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1. Enhancing Ciprofloxacin Removal: Unveiling the Potential of Graphene Oxide Synthesized from Cassava Peels through Box-Behnken Design Optimization

Author: Rinawati Rinawati, Buhani Buhani, Widiarti Widiarti, Ahmad Isro, Elsa Fitrianingsih, Anisa Rahmawati, Agung Abadi Kiswandono, and Fidelis Nitti
Subjects: ciprofloxacin, adsorption, graphene oxide, cassava peel waste, box behnken design, Technology, Economic growth, development, planning, HD72-88
Abstract: The adsorption of ciprofloxacin from an aqueous solution using graphene oxide as an adsorbent derived from cassava peel waste using a modified Hummers method was described. The properties of the adsorbent were characterized using Fourier-Transform Infrared Spectroscopy, X-ray diffraction, Raman Spectroscopy and Scanning Electron Microscopy-Energy Dispersive X-ray techniques. The influence of the operational variables including potential of hydrogen, adsorbent mass, and contact time in the adsorption of ciprofloxacin was evaluated by response surface methodology. In particular, the interactions between the operational variables were evaluated using the Box-Behnken Design to determine the optimum conditions. The results indicated that the optimum conditions were achieved at pH 3, contact time of 20 minutes, using 35 mg of graphene oxide adsorbent, resulting in an adsorption efficiency of 91.71%. The results demonstrated that the graphene oxide material derived from cassava peel waste can be effectively used as an adsorbent for ciprofloxacin from aqueous solutions.
Published: 2024
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2. Penerapan Model Geographically Weighted Logistic Regression dengan Fungsi Pembobot Adaptive Gaussian Kernel pada Data Kemiskinan

Author: Nunung Nurhasanah, Widiarti Widiarti, Dina Eka Nurvazly, and Mustofa Usman
Subjects: gwlr, adaptive gaussian kernel, poverty, Mathematics, QA1-939
Abstract: Regression analysis is one statistical method used to determine the relationship between a dependent variable and one or more independent variables. Dependent variables that are categorical are analyzed using logistic regression analysis. Geographically Weighted Logistic Regression (GWLR) is a method that is a local version of logistic regression, where location factors are considered. This method assumes that the dependent variable data are distributed binomially. In this study, the GWLR method is used to determine the factors influencing the poverty percentage in West Java Province in 2022 using an adaptive Gaussian kernel weighting function. The variables used are per capita expenditure, average length of schooling, Gross Regional Domestic Product (GRDP) per capita, and population density. The results of this study indicate that the variables of per capita expenditure, Gross Regional Domestic Product (GRDP) per capita, and population density significantly influence the poverty percentage in West Java Province in 2022.
Published: 2024
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3. Retinoblastoma with and without Extraocular Tumor Extension

Author: Swathi Kaliki, MD, Vijitha S. Vempuluru, MD, Ido Didi Fabian, MD, Elhassan Abdallah, MD, Shehu U. Abdullahi, MD, Rula A. Abdulqader, MD, Aminatu A. Abdulrahaman, MD, Sherif Abouelnaga, MD, Dupe S. Ademola-Popoola, FMCOph, FWACS, Adedayo Adio, FWACS, Mahmoud A. Afifi, MD, Armin R. Afshar, MD, Priyanka Aggarwal, MD, Ada E. Aghaji, FMCOph MSc, Alia Ahmad, MRCPCH UK, Marliyanti N.R. Akib, MD, Adeseye M. Akinsete, MBBS, Lamis Al Harby, MD, Saleh A. Al Mesfer, MD, Mouroge H. Al Ani, MD, Silvia Alarcón Portabella, MD, Safaa A.F. Al-Badri, MD, Ana Patricia A. Alcasabas, MD, Saad A. Al-Dahmash, MD, Amanda Alejos, MD, Ernesto Alemany-Rubio, MD, Amadou I. Alfa Bio, MD, Yvania Alfonso Carreras, MD, Christiane E. Al-Haddad, MD, Hamoud H.Y. Al-Hussaini, MD, MSc, Amany M. Ali, MD, Donjeta B. Alia, MD, Mazin F. Al-Jadiry, MD, Usama Al-Jumaly, MD, Hind M. Alkatan, MD, Charlotta All-Eriksson, MD, PhD, Ali A.R.M. Al-Mafrachi, FIBMS, Argentino A. Almeida, MD, Khalifa M. Alsawidi, MD, Athar A.S.M. Al-Shaheen, MD, Entissar H. Al-Shammary, MD, Doreen Amankwaa-Frempong, MBChB, Primawita O. Amiruddin, MD, Inggar Armytasari, MD, Nicholas J. Astbury, FRCS, FRCOphth, Hatice T. Atalay, MD, Eda Ataseven, MD, La-ongsri Atchaneeyasakul, MD, Rose Atsiaya, OCO, Rudolf Autrata, MD, PhD, Julia Balaguer, MD, PhD, Ruhengiz Balayeva, PhD, Honorio Barranco, MD, PhD, Paulina Bartoszek, MD, Katarina Bartuma, MD, PhD, Covadonga Bascaran, MD, MSc, Nikolaos E. Bechrakis, MD, Maja Beck Popovic, MD, Ainura S. Begimkulova, MD, Sarra Benmiloud, MD, Rokia C. Berete, MD, PhD, Jesse L. Berry, MD, Anirban Bhaduri, MD, Sunil Bhat, MBBS, MD, Arpita Bhattacharyya, MD, Eva M. Biewald, MD, Elaine Binkley, MD, Sharon Blum, MD, Nadia Bobrova, MD, H. Culver Boldt, MD, Maria Teresa B.C. Bonanomi, MD, PhD, Gabrielle C. Bouda, MD, Hédi Bouguila, MD, PhD, Rachel C. Brennan, MD, Bénédicte G. Brichard, MD, PhD, Jassada Buaboonnam, MD, Aléine Budiongo, MD, Matthew Burton, FRCOphth, Patricia Calderón-Sotelo, MD, Doris A. Calle Jara, MD, Jayne E. Camuglia, FRANZCO, Miriam R. Cano, MD, MSc, Michael Capra, FRCPI, Shani Caspi, MD, Nathalie Cassoux, MD, PhD, Guilherme Castela, MD, Luis Castillo, MD, Jaume Català-Mora, MD, PhD, Isabel Caviedes, MD, Arthika Chandramohan, MD, Guillermo L. Chantada, MD, PhD, Shabana Chaudhry, MD, Bhavna Chawla, MD, Wensi Chen, MD, Faraja S. Chiwanga, MSc, Tsengelmaa Chuluunbat, MD, PhD, Krzysztof Cieslik, MD, Antony Clark, FRANZCO, Ruellyn L. Cockcroft, MB ChB , M Med Paed, Codruta Comsa, MD, Maria G. Correa Llano, MD, Timothy W. Corson, PhD, Line Couitchere, MD, Kristin E. Cowan-Lyn, MD, MBBS, Monika Csóka, MD, PhD, Wantanee Dangboon, MD, Anirban Das, MD, Pranab Das, MD, Sima Das, MS, Jacquelyn M. Davanzo, BSN, BSPH, Alan Davidson, MBChB, MPhil, Sonia De Francesco, MD, Patrick De Potter, MD, PhD, Karina Q. Delgado, MD, PhD, Hakan Demirci, MD, Laurence Desjardins, MD, Rosdali Y. Diaz Coronado, MD, Helen Dimaras, PhD, Andrew J. Dodgshun, M Phil, Carla R. Donato Macedo, MD, Monica D. Dragomir, MD, PhD, Yi Du, MD, Magritha Du Bruyn, MD, Johannes P. Du Plessis, MMed (Paed), Gagan Dudeja, MBBS, MS, Katrin Eerme, MD, I Wayan Eka Sutyawan, MD, Asmaa El Kettani, MD, Amal M. Elbahi, MD, James E. Elder, MBBS, Alaa M. Elhaddad, MD, PhD, Moawia M.A. Elhassan, MD, Mahmoud M. Elzembely, MD, Connor Ericksen, MD, Vera A. Essuman, FWACS, Ted Grimbert A. Evina, MD, Ifeoma R. Ezegwui, FMCOph, FWACS, FAEH, Zehra Fadoo, MBBS, Adriana C. Fandiño, MD, Mohammad Faranoush, MD, Oluyemi Fasina, FWACS, Delia D.P.G. Fernández, MSc, Ana Fernández-Teijeiro, MD, PhD, Allen Foster, FRCOphth, Shahar Frenkel, MD, PhD, Ligia D. Fu, MD, Soad L. Fuentes-Alabi, MD, MPH, Juan L. Garcia, MSc, David García Aldana, MD, Henry N. Garcia Pacheco, MD, Jennifer A. Geel, MBChB, MMed, Fariba Ghassemi, MD, Ana V. Girón, MD, Marco A. Goenz, MD, Aaron S. Gold, OD, Hila Golberg, MD, Glen A. Gole, MD, FRANZCO, Nir Gomel, MD, Efren Gonzalez, MD, Graciela Gonzalez Perez, MD, Liudmira González-Rodríguez, MD, Malka Gorfine, PhD, Jaime Graells, MD, Pernille A. Gregersen, MD, Nathalia D.A.K. Grigorovski, MD, Koffi M. Guedenon, MD, D Sanjeeva Gunasekera, MD, Ahmet K. Gündüz, MD, Himika Gupta, MD, Sanjiv Gupta, MS, Vineeta Gupta, MD, Theodora Hadjistilianou, MD, Patrick Hamel, MD, Syed A. Hamid, FCPS, Norhafizah Hamzah, MSc, Eric D. Hansen, MD, J William Harbour, MD, M. Elizabeth Hartnett, MD, Murat Hasanreisoglu, MD, Sadiq Hassan, MD, FWACS, Shadab Hassan, FRCS, FCPS, Wojciech Hautz, MD, Huda A. Haydar, CHD, Stanislava Hederova, MD, Laila Hessissen, MD, Hoby Lalaina, MD, Suradej Hongeng, MD, Diriba F. Hordofa, MD, G. Baker Hubbard, MD, Marlies Hummlen, MD, Kristina Husakova, MD, Allawi N. Hussein Al-Janabi, MD, Affiong A. Ibanga, MB.BCh, FMCOph, Russo Ida, MD, Vesna R. Ilic, MD, Ziyavuddin Islamov, MD, Vivekaraj Jairaj, DNB, Teyyeb A. Janjua, MD, FCPS, FRCSEd, Irfan Jeeva, FRCOphth, Xunda Ji, MD, Dong Hyun Jo, MD, PhD, Michael M. Jones, MD, PhD, FRANZCO, Theophile B. Amani Kabesha, MD, PhD, Rolande L. Kabore, MD, Abubakar Kalinaki, MD, Pius Kamsang, MD, Mehmet Kantar, MD, Noa Kapelushnik, MD, Tamar Kardava, PhD, Rejin Kebudi, MD, Jonny Keomisy, MD, Tomas Kepak, MD, Petra Ketteler, MD, Zohora J. Khan, MD, Hussain A. Khaqan, MD, Vikas Khetan, FRCS, FACS, Alireza Khodabande, MD, Zaza Khotenashvili, MD, Jonathan W. Kim, MD, Jeong Hun Kim, MD, PhD, Hayyam Kiratli, MD, Tero T. Kivelä, MD, Artur Klett, MD, PhD, Irem Koç, MD, Jess Elio Kosh Komba Palet, MD, Dalia Krivaitiene, MD, PhD, Mariana Kruger, Mmed Paed, PhD, Kittisak Kulvichit, MD, Mayasari W. Kuntorini, MD, Alice Kyara, BA, Geoffrey C. Lam, FRANZCO, Scott A. Larson, MD, Slobodanka Latinović, MD, PhD, Kelly D. Laurenti, MD, Yotam Lavi, MD, PhD, Alenka Lavric Groznik, MD, Amy A. Leverant, MD, Cairui Li, MD, Kaijun Li, MD, Ben Limbu, MD, Chun-Hsiu Liu, MD, Quah Boon Long, FRCS (Ed), MMed ( Ophth), FAMS, Juan P. López, MD, Robert M. Lukamba, MD, Sandra Luna-Fineman, MD, Delfitri Lutfi, MD, Lesia Lysytsia, MD, Shiran Madgar, MD, George N. Magrath, MD, Amita Mahajan, MD, Puja Maitra, MD, Erika Maka, MD, Emil K. Makimbetov, MD, Azza M.Y. Maktabi, MD, Carlos Maldonado, MD, Ashwin Mallipatna, MD, Rebecca Manudhane, MD, Lyazat Manzhuova, MD, Nieves Martín Begue, MD, PhD, Sidra Masud, MBBS, Ibrahim O. Matende, MD, M. Med (Oph), Clarissa C.D.S. Mattosinho, MD, Marchelo Matua, BAPH, Ismail Mayet, MD, Freddy B. Mbumba, MD, MMed Paed, John D. McKenzie, MD, Azim Mehrvar, MD, Aemero A. Mengesha, MD, Vikas Menon, MD, Gary John V.D.D. Mercado, MD, Marilyn B. Mets, MD, Edoardo Midena, MD, PhD, Audra Miller, MD, Divyansh K.C. Mishra, DNB, Furahini G. Mndeme, MD, Ahmed A. Mohamedani, FRCPath, Mona T. Mohammad, MD, FRCS, Annette C. Moll, MD, PhD, Margarita M. Montero, MD, Claude Moreira, MD, PhD, Prithvi Mruthyunjaya, MD, MHS, Mchikirwa S. Msina, MMed Ophth, Gerald Msukwa, MMed Ophth, Sangeeta S. Mudaliar, DNB Pediatric, Hassan Muhammad, MD, Kangwa I. Muma, MMed Ophth, FCOphth, Francis L. Munier, MD, Timothy G. Murray, MD, MBA, Kareem O. Musa, FWACS, FMCOphth, FICO, Asma Mushtaq, MD, Anne A. Musika, MD, Hamzah Mustak, MD, Tajudeen Mustapha, MBBS, FWACS, Okwen M. Muyen, MD, Khumo H. Myezo, Msc, Gita Naidu, MMed Paed, PhD, Natasha Naidu, MBCHB, FCS Ophthalmol, Akshay Gopinathan Nair, MD, Sundaram Natarajan, FRCS, Larisa Naumenko, MD, PhD, Paule Aïda Ndoye Roth, MD PhD, Yetty M. Nency, MD, Vladimir Neroev, MD, PhD, Yvonne Ng, MBChB ( Auckland) , FRANZCO, Marina Nikitovic, MD, PhD, Elizabeth D. Nkanga, FMCOph, Henry E. Nkumbe, MD, Marcel N. Numbi, MD, Kalle Nummi, MD, Murtuza Nuruddin, FRCS, Mutale Nyaywa, MD, MMed Ophth, FCOphth, Chinsisi Nyirenda, MD, Ghislaine Obono-Obiang, MD, Scott C.N. Oliver, MD, Joaquin Ooporto, MD, Miriam Ortega-Hernández, MD, Alexander Oscar, MD, Diego Ossandon, MD, Halimah Pagarra, MD, PhD, Vivian Paintsil, FWACP, Luisa Paiva, MD, Mahesh Shanmugam Palanivelu, FRCSED, Ruzanna Papyan, MD, Raffaele Parrozzani, MD, PhD, Claudia R. Pascual Morales, MD, Katherine E. Paton, MD, FRCSC, Jacob Pe'er, MD, Jesús Peralta Calvo, MD, Sanja Perić, MD, PhD, Chau T.M. Pham, MD, Remezo Philbert, MD, David A. Plager, MD, Pavel Pochop, MD, PhD, Rodrigo A. Polania, MD, Vladimir Polyakov, MD, Jimena Ponce, MD, Ali O. Qadir, MD, Seema Qayyum, FCPS, Jiang Qian, MD, Ardizal Rahman, MD, Purnima Rajkarnikar, MD, Rajesh Ramanjulu, MD, Aparna Ramasubramanian, MD, Marco A. Ramirez-Ortiz, MD, MPH, Jasmeen K. Randhawa, BA, Léa Raobela, MD, Riffat Rashid, MS, M. Ashwin Reddy, FRCOphth, Lorna A. Renner, FRCPCH (UK), David Reynders, MD, Dahiru Ribadu, FMCOph, Petra Ritter-Sovinz, MD, Anna Rogowska, MD, Duangnate Rojanaporn, MD, Livia Romero, MD, Soma R. Roy, DCO, Raya H. Saab, MD, Svetlana Saakyan, MD, PhD, Ahmed H. Sabhan, MD, Mandeep S. Sagoo, FRCS (Ed), Azza M.A. Said, MD, Rohit Saiju, MD, Beatriz Salas, MD, Sonsoles San Román Pacheco, MD, Gissela L. Sánchez, MD, Alma Janeth Sanchez Orozco, MD, Phayvanh Sayalith, MD, Trish A. Scanlan, MRCPI, MSc, Christoph Schwab, MD, Ahad Sedaghat, MD, Rachna Seth, DNB MNAMS, Mariana Sgroi, MD, Ankoor S. Shah, MD, PhD, Shawkat A. Shakoor, MS, Manoj K. Sharma, MD, Sadik T. Sherief, MD, Carol L. Shields, MD, David Sia, MB ChB, FRANZCO, Sorath Noorani Siddiqui, MD, Sidi Sidi cheikh, MD, PhD, Sónia Silva, MD, Arun D. Singh, MD, Usha Singh, MS, Penny Singha, MD, Rita S. Sitorus, MD, PhD, Alison H. Skalet, MD, PhD, Hendrian D. Soebagjo, MD, PhD, Tetyana Sorochynska, MD, PhD, Grace Ssali, MD, Andrew W. Stacey, MD, Sandra E. Staffieri, PhD, Erin D. Stahl, MD, David M. Steinberg, PhD, David K. Stones, MBChB, FCPaed, Caron Strahlendorf, MD, Maria Estela Coleoni Suarez, MD, Sadia Sultana, FCPS, Xiantao Sun, MD, Rosanne Superstein, MD, Eddy Supriyadi, MD, PhD, Supawan Surukrattanaskul, MD, Shigenobu Suzuki, MD, PhD, Karel Svojgr, MD, PhD, Fatoumata Sylla, MD, Gevorg Tamamyan, MD, PhD, Deborah Tan, MBBS, Alketa Tandili, MD, PhD, Jing Tang, MD, Fanny F. Tarrillo Leiva, MD, Maryam Tashvighi, MD, Bekim Tateshi, MD, PhD, Kok Hoi Teh, MD, Edi S. Tehuteru, MD, Luiz F. Teixeira, MD, Manca Tekavcic Pompe, MD, PhD, Abdullah Dahan M. Thawaba, MD, Tuyisabe Theophile, MSc, Helen Toledano, MBChB, Doan L. Trang, MD, Fousseyni Traoré, MD, Devjyoti Tripathy, MD, Samuray Tuncer, MD, Harba Tyau-Tyau, MD, Ali B. Umar, MD, FMCPath, Emel Unal, MD, Ogul E. Uner, BA, Steen F. Urbak, MD, PhD, Tatiana L. Ushakova, MD, Rustam H. Usmanov, MD, Sandra Valeina, MD, Paola Valente, MD, Milo van Hoefen Wijsard, MD, Jacqueline Karina Vasquez Anchaya, MD, Leon O. Vaughan, FRCS (Ed), Nevyana V. Veleva-Krasteva, MD, PhD, Nishant Verma, MD, Andi A. Victor, MD, PhD, Maris Viksnins, MD, Edwin G. Villacís Chafla, MD, Victor M. Villegas, MD, Victoria Vishnevskia-Dai, MD, Keith Waddell, DM, FRCP, FRCS, FRCOphth, Amina H. Wali, MD, FMCOph Nigeria, Yi-Zhuo Wang, MD, Nutsuchar Wangtiraumnuay, MD, FICO, Julie A. Wetter, MMed Rad Onc, FCRad Onc, Widiarti P. Riono, MD, Matthew W. Wilson, MD, Amelia D.C. Wime, MD, Atchareeya Wiwatwongwana, MD, Damrong Wiwatwongwana, MD, Charlotte Wolley Dod, MD, Emily S. Wong, FCOphth HK, FHKAM, Phanthipha Wongwai, MD, PhD, Si-qi Wu, MSc, Daoman Xiang, MD, PhD, Yishuang Xiao, MSc, Bing Xu, MD, Kang Xue, MD, Antonio Yaghy, MD, Jason C. Yam, FRCSEd, Huasheng Yang, MD, Jenny M. Yanga, MD, Muhammad A. Yaqub, MD, FCPS, FRCSEd, Vera A. Yarovaya, MD, Andrey A. Yarovoy, MD, PhD, Huijing Ye, MD, Roberto I. Yee, MD, Yacoub A. Yousef, MD, Putu Yuliawati, MD, Arturo M. López, MD, Ekhtelbenina Zein, MD, Yi Zhang, MD, PhD, Katsiaryna Zhilyaeva, MD, Nida Zia, MBBS, MCPS, Othman A.O. Ziko, MD, PhD, Marcia Zondervan, MBA, Sabrina Schlüter, MD, and Richard Bowman, FRCOphth
Subjects: External beam radiotherapy, Extraocular extension, Multimodal treatment, Retinoblastoma, Tumor, Ophthalmology, RE1-994
Abstract: Purpose: To study the treatment and outcomes of children with retinoblastoma (RB) with extraocular tumor extension (RB-EOE) and compare them with RB without extraocular tumor extension (RB-w/o-EOE). Design: Multicenter intercontinental collaborative prospective study from 2017 to 2020. RB-EOE cases included those with overt orbital tumor extension in treatment-naive patients. Cases with microscopic orbital extension detected postenucleation were excluded from the study. Participants: A total of 319 children with RB-EOE and 3116 children with RB-w/o-EOE. Intervention: Chemotherapy, enucleation, exenteration, radiotherapy. Main Outcome Measures: Systemic metastasis and death. Results: Of the 3435 RB patients included in this study, 309 (9%) were from low-income countries (LIC), 1448 (42%) from lower-middle income, 1012 (29%) from upper-middle income, and 666 (19%) patients from high-income countries. There was an inverse relationship between the percentage of RB-EOE and national income level, with 96 (31%) patients from LIC, 197 (6%) lower-middle income, 20 (2%) upper-middle income, and 6 (1%) patients from high-income countries (P = 0.0001). The outcomes were statistically significant for RB-EOE compared with RB-w/o-EOE: systemic metastasis (32% vs. 4% respectively; P = 0.0001) and metastasis-related death (63% vs. 6% respectively; P = 0.0001). Multimodal treatment was the most common form of treatment (n = 177; 54%) for RB-EOE, with most cases undergoing a combination of intravenous chemotherapy and enucleation (n = 97; 30%). Adjuvant external beam radiotherapy (EBRT) after surgery (enucleation/orbital exenteration) was given in only 68 (21%) cases. Kaplan–Meier analysis for systemic metastasis and metastasis-related death in RB-EOE was 28% and 57% at 1 year, 29% and 60% at 2 years, and 29% and 61% at 3 years, respectively. Cox regression analysis revealed that the risk of death from RB-EOE was greater in patients aged >4 years than
Published: 2025
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4. Modeling and Forecasting Closing Prices of some Coal Mining Companies in Indonesia by Using the VAR(3)-BEKK GARCH(1,1) Model

Author: Wamiliana Wamiliana, Edwin Russel, Iskandar Ali Alam, Widiarti Widiarti, Tuti Hairani, and Mustofa Usman
Subjects: Vector Autoregressive, BEKK GARCH Model, Forecasting, Granger Causality, Proportion Prediction Error Covariance, Environmental sciences, GE1-350, Energy industries. Energy policy. Fuel trade, HD9502-9502.5
Abstract: Today, coal is the main source of energy in both developed and developing countries. The use of coal fuel for power generation and industry continues to increase. This research will discuss the closing price relationship model for the share prices of two coal companies in Indonesia, namely ABM and IND_E, from January 2018 to July 2023. The modeling used is a multivariate time series approach. From the results of the data analysis, the best model that fits the data is the VAR(3)-BEKK GARCH(1,1). Based on this best model, further analysis of Granger causality, impulse response function (IRF), and forecasting for the next 30 periods as well as the proportion of prediction error covariance are discussed.
Published: 2024
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5. Evaluasi dan Monitoring Bangunan Ukur Debit pada Saluran Primer Kesilir Kecamatan Wuluhan

Author: Denok Nurul Intifadah, Wiwik Yunarni Widiarti, and Widiarti, Saifurridzal
Subjects: kalibrasi, crumpweir, cipoletti, Engineering (General). Civil engineering (General), TA1-2040
Abstract: The most often problem that is usually occurred in the field is damage of discharge measuring building. In Kesilir’s primary channel, they are crumpweir dan cipoletti measuring structure that have decreased in fuction. This research was conducted by analyzing the discharge obtained from field data collection, wet cross-section area (A), flow velocity (v) and peilscal height (h). Callibration analysis of discharge measuring building is carried out by differentiating between the equation resulting from the graph using power function. The research result in the measurement differences of the upstream and downstream of the channel at two locations. The callibration coefficient of the crumpweir is 0.39 and the cipolleti is 0.72 respectvely.
Published: 2023
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6. The Effect of Air Injection Flowrate on Nitrate Synthesis with The Addition of Fe2+ Ions Using Plasma Electrolysis

Author: Harianingsih Harianingsih, Sulistyawan Vera Noviana, Kusumaningrum Maharani, Widiarti Nuni, Pangestu Indra Sakti, Putra Muhammad Rizky Fahrizal, Ritmadanti Afifah, and Kurniawan Tonni Agustiono
Subjects: Environmental sciences, GE1-350
Abstract: This study aims to determine the effect of air flow rate on nitrate synthesis with the addition of Fe2+ ions using the plasma electrolysis method. Nitrate synthesis usually uses conventional technology that causes air emissions. So that plasma electrolysis technology is needed that does not cause emissions and is environmentally friendly. The methods used in this study include designing a plasma electrolysis reactor using 0.02 M K2SO4 electrolyte, testing the plasma electrolysis reactor to determine the formation of a glow discharge zone as an indicator of the nitrate synthesis process, testing nitrate production using a UV VIS spectrophotometer and •OH radicals using HPLC. The air reaction rate at variations of 0.2 Lmen-1, 0.4 Lmen-1, 0.6 Lmen-1, 0.8 Lmen-1 and 1 Lmen-1 was injected into the reactor. The concentration of Fe2+ ions at 10 ppm, 20 ppm, 30 ppm, 40 ppm and 50 ppm was analyzed to determine the effectiveness of the ion. The results obtained were that the highest nitrate at 400 Watt power was 2976 ppm, at 500 Watt power was 3063 ppm, and at 600 Watt power was 3373 ppm. the highest nitrate production was achieved at a concentration of 30 ppm with a result of 2785 ppm, followed by a concentration of 40 ppm with a result of 2645 ppm, a concentration of 20 ppm with a result of 2512 ppm, a concentration of 10 ppm with a result of 2478 ppm, and a concentration of 50 ppm with a result of 2364 ppm..
Published: 2024
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7. An Assessment of Urban Forest Landscape Services for Green Space Management Improvement in Bandung City, West Java, Indonesia

Author: Afrianti Chairunnisa, Widiarti Novita Mellinia, Akbar Indria Zhafirah, Rachmanto Eurico Pratama, Hanif Muhammad Faig, Amin Rahmat Akhirul, Kaswanto Kaswanto, Wiyoga Harityas, and Mosyaftiani Amarizni
Subjects: Microbiology, QR1-502, Physiology, QP1-981, Zoology, QL1-991
Abstract: In the Bandung metropolitan area, urban forests (UFs) play a crucial role in providing landscape services, especially within the Babakan Siliwangi Urban Forest (BSUF). The BSUF is currently facing multiple development challenges, necessitating scientific evidence to elucidate its role in Bandung's urban landscape. This research analyzes the BSUF’s function in carbon storage, carbon sequestration, and oxygen production and to formulate management recommendations to provide optimal future benefits. Data collection was carried out in 14 sample plots and i-Tree Eco was used to analyze landscape services and predict future vegetation structure based on planned plantings. The findings reveal that (1) BSUF has a high tree diversity, with a 3.3 Shannon index and 41 tree species identified; (2) it stores 381 tons of carbon, sequesters 25.17 tons of carbon annually, and produces 65.07 tons of oxygen per year; (3) to enhance landscape services value for the next 30 years, a minimum 300 trees must be planted per year. These results demonstrate the BSUF’s significance and the importance of tree diversity in sustaining landscape services provided by UF. Additionally, this research introduces i-Tree Eco as a valuable tool for conducting vegetation analysis, aiding stakeholders in monitoring and formulating improved landscape management strategies.
Published: 2024
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8. Design of Unipolar Pure Sine Wave Inverter with Spwm Method Based On Esp32 Microcontroller As a Support of The Ebt System On Ship

Author: Ahmad Putra Zindhu Maulana, Nugraha Anggara Trisna, Widiarti Yuning, Safaroz Wafiq, and Sobhita Rama Arya
Subjects: Environmental sciences, GE1-350
Abstract: Along with developments in the maritime sector, especially on ships, the need for electric power on board will be very diverse. The use of diesel engines as power plants requires fuel to drive a diesel while the use of fuel in ships produced from petroleum processing is limited. Efforts to reduce the use of fuel is by implementing new renewable energy as independent electricity on ship. In EBT inverter technology plays an important role in converting DC voltage to AC voltage. In the inverter, the use of microcontrollers as drivers to generate PWM signals continues to develop. One of the developments of the microcontroller is ESP32. The problem that often occurs in inverters is that the output voltage is unstable. In addition to maximizing the performance of the inverter, it is necessary to add a protection system to reduce the risk of damage to the inverter or the load. Therefore, an inverter was made using the ESP32 microcontroller driver with the addition of protection and the fuzzy method as a voltage stabilizer. This inverter will change the 12 Vdc to 220 vac. In the Matlab simulation, the inverter can change the 12 vdc to 12 vpeak with a carrier signal of 20 khz and a reference signal of 50 hz. From the results of the inverter output will be changed to 220 vac using a step up transformer. The research overlay is being able to make a pure sine wave SPWM inverter using an ESP32 driver with a stable voltage.
Published: 2024
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9. Batik classification using KNN algorithm and GLCM features extraction

Author: Wijaya David and Widiarti Anastasia Rita
Subjects: Environmental sciences, GE1-350
Abstract: Batik is one of the Indonesian cultures that has been recognized by UNESCO as an intellectual right of Indonesia. The popularity of batik internationally raises concerns about the Indonesian people’s understanding of batik if Indonesian people only refer to all types of batik just as ‘batik’. By utilizing K-Nearest Neighbour (KNN) algorithm which is a simple classification algorithm, then a system can be created that can classify batik types. The first step of KNN is training, which stores each training pattern. The second step is classification, whenever classifying a pattern, KNN examine all training patterns to determine the K closest patterns using certain calculations such as Euclidean Distance and Manhattan Distance. Before classification, a characteristic that represents a pattern is needed. Gray-Level Co-Occurrence Matrix (GLCM) is an algorithm that has proven to be very powerful as a feature descriptor in representing the texture characteristic of an image. This research experiments with the value of K in KNN = 1, 3, 5, and 7 with the distance calculation using Euclidean and Manhattan. The GLCM characteristic used are Entropy, Energy, Contrast, Homogeneity, Dissimilarity, Correlation, ASM, and the average of each characteristic. From the research that has been done, the system created obtained the highest accuracy of 75% with the combination of parameters; pixel distance = 7, K value = 1, 1st fold as test data and 2nd and 3rd fold as training data, and by using StandardScaler. But despite getting decent accuracy, there is still a need for further research to improve the accuracy of batik classification.
Published: 2024
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10. Pengaruh motivasi belajar dan konsep diri terhadap prestasi belajar mata pelajaran matematika siswa

Author: Ulfah Musyaropah, Nurhayati Adiratna Kusuma, Asti Iryanti Putri, Widiarti Widiarti, Yayi Tresnatri, and Ahmad Muhammad Diponegoro
Subjects: learning achievement, learning motivation, self-concept, Psychology, BF1-990
Abstract: Abstract: This study aims to examine the effect of learning motivation and self-concept on student achievement in mathematics at SMK Muhammadiyah 2 Sleman. This research uses a quantitative approach with a cross sectional study method. The population of this study were students of SMK Muhammadiyah 2 Sleman. The sampling technique in this study used saturated sampling. The sample in this study amounted to 40 students. The data collected by using a learning motivation scale and a self-concept scale with a Likert scale response type. Meanwhile, students' mathematic test scores used as the data of learning achievement. The data analysis technique used in this research is multiple linear regression analysis. The results showed that simultaneously there is a very significant influence between learning motivation and self-concept on student achievement in mathematics at SMK Muhammadiyah 2 Sleman. The contribution of learning motivation and self-concept to student achievement is 63,4%. The implication of this research is to Give an information that the student study motivation is important to be improved to boost the student study performance. Abstrak: Penelitian bertujuan untuk menguji pengaruh motivasi belajar dan konsep diri terhadap prestasi belajar mata pelajaran matematika siswa SMK Muhammadiyah 2 Sleman. Penelitian ini menggunakan pendekatan kuantitatif dengan metode cross sectional study. Populasi penelitian ini adalah siswa di SMK Muhammadiyah 2 Sleman. Teknik pengambilan sampel pada penelitian ini menggunakan sampling jenuh. Sampel pada penelitian ini berjumlah 40 siswa. Pengumpulan data menggunakan skala motivasi belajar dan skala konsep diri dengan jenis penskalaan respon skala likert. Sedangkan skala prestasi belajar menggunakan hasil nilai ujian mata pelajaran matematika. Teknik analisis data yang digunakan pada penelitian adalah analisis regresi linear berganda. Hasil penelitian secara simultan terdapat pengaruh yang sangat signifikan antara motivasi belajar dan konsep diri terhadap prestasi belajar siswa mata pelajaran matematika siswa di SMK Muhammadiyah 2 Sleman. Besarnya kontribusi motivasi belajar dan konsep diri terhadap prestasi belajar siswa adalah sebesar 63,4%. Implikasi dari penelitian ini yaitu untuk memberikan informasi bahwa motivasi belajar siswa penting untuk ditingkatkan guna meningkatkan prestasi belajar siswa.
Published: 2022
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11. Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia

Author: Mustofa Usman, Luvita Loves, Edwin Russel, Muslim Ansori, Warsono Warsono, Widiarti Widiarti, and Wamiliana Wamiliana
Subjects: VAR model, VECMX, time series, Granger causality, Impulse response function, Environmental sciences, GE1-350, Energy industries. Energy policy. Fuel trade, HD9502-9502.5
Abstract: Time series modeling analysis is one of the methods to forecast based on past data and conditions. The analytical tool that is commonly used to forecast multivariate time series data is the Vector Autoregressive (VAR) model. However, when the variables have cointegration and stationary at the first difference value, then the VAR model is modified into the Vector Error Correction Model (VECM). In VECM, all variables can be used as endogenous variables. If exogenous variables are involved in the VECM model, then the model is called as Vector Error Correction Model with Exogenous variables (VECMX). In the present study, a time series modeling analysis was used to analyze the price of gasoline, the money supply in a broad sense (M2), oil and gas exports, and consumption imports over the years from 2012 to 2020. By using information on the criteria of Akaike Information Criterion Corrected, Hannan–Quinn Criterion, Akaike Information Criterion, and Schwarz Bayesian Criterion, the best VAR(p) model is obtained with order 3, or lag 3. Based on the VAR(3) model, the cointegration test is conducted, and the result shows that there is a long-term relationship among variables, namely, there is a cointegration relationship between variables with rank = 1. Based on the cointegration rank = 1 and the smallest value of the information criteria and comparison of some candidate best models, namely, VECMX(2,1), VECMX(2,2), VECMX(3,1), VECMX(3,2), and VECMX(4,1), we found that the best model is VECMX(3,1) with lag 3 for endogenous variables and lag 1 for exogenous variables. Based on this best model, further analysis of Granger causality, Impulse Response Function (IRF), and forecasting is discussed.
Published: 2022
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12. Homogeneity and Possible Replacement of Populations of the Dengue Vectors Aedes aegypti and Aedes albopictus in Indonesia

Author: Triwibowo Ambar Garjito, Widiarti Widiarti, Muhammad Choirul Hidajat, Sri Wahyuni Handayani, Mujiyono Mujiyono, Mega Tyas Prihatin, Rosichon Ubaidillah, Mohammad Sudomo, Tri Baskoro Tunggul Satoto, Sylvie Manguin, Laurent Gavotte, and Roger Frutos
Subjects: Aedes aegypti, Aedes albopictus, Indonesia, cox1, internal transcribed spacer 2 (ITS2), Microbiology, QR1-502
Abstract: Currently, Aedes aegypti, the principal vector of dengue virus in Indonesia, has spread throughout the archipelago. Aedes albopictus is also present. Invasion and high adaptability of the Aedes mosquitoes to all of these areas are closely related to their ecology and biology. Between June 2016 and July 2017, larval and adult mosquito collections were conducted in 43 locations in 25 provinces of Indonesia using standardized sampling methods for dengue vector surveillance. The samples collected were analyzed for polymorphism and phylogenetic relationship using the mitochondrial cox1 gene and the nuclear ribosomal internal transcribed spacer 2 (ITS2). Almost all Ae. aegypti samples collected in this study (89%) belonged to the same haplotype. A similar situation is observed with the nuclear ITS2 marker. Populations of Ae. aegypti characterized few years ago were genetically different. A closely related observation was made with Aedes albopictus for which the current populations are different from those described earlier. Ae. aegypti populations were found to be highly homogenous all over Indonesia with all samples belonging to the same maternal lineage. Although difficult to demonstrate formally, there is a possibility of population replacement. Although to a lower extent, a similar conclusion was reached with Ae. albopictus.
Published: 2021
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13. Genetic homogeneity of Anopheles maculatus in Indonesia and origin of a novel species present in Central Java

Author: Triwibowo Ambar Garjito, Umi Widiastuti, Mujiyono Mujiyono, Mega Tyas Prihatin, Widiarti Widiarti, Riyani Setyaningsih, Siti Alfiah, Barandi Sapta Widartono, Din Syafruddin, Tri Baskoro Tunggul Satoto, Laurent Gavotte, Michael J. Bangs, Sylvie Manguin, and Roger Frutos
Subjects: Anopheles maculatus, Maculatus Group, Indonesia, Malaria, Infectious and parasitic diseases, RC109-216
Abstract: Abstract Background Anopheles maculatus (s.s.) is an important vector of malaria in Indonesia. Previously it was considered the only member of the Maculatus Group present in Indonesia. A novel species was recently identified in the Kulon Progo District in Central Java. Until recently, few investigations have been conducted looking at An. maculatus genetic diversity in Indonesia, including allopatric island populations. Methods Indonesian An. maculatus (s.l.) samples were collected in several locations in Java, Lesser Sunda Island group, Sumatra and in Kulon Progo (Yogyakarta, central Java) where a novel species has been identified. Samples from a 30-year-old colony of the Kulon Progo population were also included in the analysis. Maximum-likelihood analysis established the phylogenies of the ITS2 (nuclear) and cox1 (mitochondrial) markers. Putative times of separation were based on cox1 genetic distances. Results Two species of the Maculatus Group are present in Indonesia. The novel sibling species is more closely related to Anopheles dispar than to An. maculatus (s.s.). Anopheles maculatus (s.s.) samples are homogeneous based on the ITS2 sequences. Indonesian samples and An. dispar belong to the same cox1 maternal lineage and differ from all other known members of the Maculatus Group. Divergence time between the different populations found in Java was estimated using an established cox1 mutation rate. Conclusions A novel species within the Maculatus Group, most closely related to An. dispar, is confirmed present in the Kulon Progo area of Central Java. The divergence of this species from An. maculatus (s.s.) is explained by the stable refugia in the Kulon Progo area during the quaternary period of intense volcanic activity throughout most of Java. This novel species awaits detailed morphological description before applying a formal species name. For the interim, it is proposed that the Kulon Progo population be designated An. maculatus var. menoreh to distinguish it from An. maculatus (s.s.).
Published: 2019
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14. The Role of Subcutaneous Furosemide in Heart Failure Management: A Systematic Review

Author: Widiarti, Wynne, Saputra, Pandit Bagus Tri, Ariyanto, Melissa Valentina, Savitri, Cornelia Ghea, Multazam, Chaq El Chaq Zamzam, Putranto, Johanes Nugroho Eko, and Alkaff, Firas Farisi
Published: 2024
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15. Analisa Kesesuaian Lahan Dan Potensi Perkebunan Kelapa Sawit di Kabupaten Tanah Laut Menggunakan Sistem Informasi Geografis

Author: Widiarti Widiarti and Nurlina Nurlina
Subjects: Sistem Informasi Geografis, Kesesuaian lahan, Metode Matching, Physics, QC1-999
Abstract: Kalimantan Selatan mempunyai potensi untuk perkebunan kelapa sawit yang cukup luas. Wilayah yang mempunyai potensi perkebunan kelapa sawit ini yaitu Kabupaten Tanah Laut. Penelitian ini dilakukan tentang kesesuaian dan potensi perkebunan kelapa sawit di Kabupaten Tanah Laut menggunakan sistem informasi geografis. Penelitian ini bertujuan untuk menganalisa kesesuaian lahan dengan parameter curah hujan, suhu udara, jenis tanah, dan topografi untuk perkebunan kelapa sawit di Kabupaten Tanah Laut menggunakan sistem informasi geografis serta mengetahui potensi perkebunan kelapa sawit di Kabupaten Tanah Laut. Metode yang digunakan untuk analisa kesesuaian lahan dan potensi perkebunan kelapa sawit yaitu metode matching. Hasil pengolahan data didapatkan luas kesesuaian lahan dalam kategori sesuai (S1) sekitar 313.495,859 ha (81,58%), cukup sesuai (S2) sekitar 57.583,805 ha (14,98%), sesuai marginal (S3) sekitar 12.189,264 ha (3,17%) dan tidak sesuai (N) sekitar 1.023,398 ha (0.27%). Luas lahan yang mempunyai potensi perkebunan yaitu lahan dalam kategori berpotensi (P1) seluas 65.830,00 ha (18,13%), cukup berpotensi (P2) seluas 33.050,00 ha (9.10%), dan berpotensi marginal (P3) seluas 4.996,86 ha (1,38%).
Published: 2017

16. Evaluation of electrodeposition synthesis of gold nanodendrite on screen-printed carbon electrode for nonenzymatic ascorbic acid sensor

Author: Ariasena, Eduardus, Raditya, Aldyla Nisa, Salsabila, Nadia, Asih, Geolita Ihsantia Ning, Uperianti, Sari, Rizky Indah, Handayani, Murni, Siburian, Rikson, Kurniawan, Cepi, Widiarti, Nuni, Irkham, Hartati, Yeni Wahyuni, and Anshori, Isa
Published: 2024
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17. Kepadatan Larva Nyamuk Vektor sebagai Indikator Penularan Demam Berdarah Dengue di Daerah Endemis di Jawa Timur

Author: Arum Sih Joharina and Widiarti Widiarti
Subjects: Infectious and parasitic diseases, RC109-216
Abstract: Dengue Hemorrhagic Fever (DHF) is one of the serious health problems in Indonesia.There are always DHF cases every year. East Java is a province with high cases of DHFevery year, with the peak of burden was 86,52 cases per 100.000 people in 2010. Thisstudy, conducted in 2011, was aimed to know the larval density figure and key container inthe dengue endemic areas in East Java. In total, there were 10 villages from three districts(Tulungagung, Malang and Kediri) were surveied. One hundred houses were visualysurveied to count the larvae indices: House Index (HI), Container Index (CI), and BreteauIndex (BI) based on the WHO regulation. Larvae-Free Index based on the IndonesianMinistry of Health regulation was also measured. The larvae indices measured indicatedthat eight villages were categorized as middle risk (density figure 5) and two villages(Bago Village from Tulungagung and Mojoroto Village from Kediri) were categorized ashigh risk (density figure 6). Cement bath tub was the key container of all location. Basedon these results known that three districts were potential for dengue transmission.
Published: 2015
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18. Reconstruction of The Ethno-STEM Integrated Inquiry-Based Project Learning Model (Ethno-STEM IBPjLM) for the Topic of Herbal Tea Aroma Compounds as Global Local Wisdom

Author: Sudarmin, Sudarmin, Harjono, Harjono, Rahayu, S., Widiarti, H. R., Setiawan, B., Huatagalung, F. D., Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Habiddin, Habiddin, editor, Suwono, Hadi, editor, and Farida, Nani, editor
Published: 2024
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19. Design of Biofouling Level Classification System Using Haar-Cascade Classifier And Local Binary Pattern Histogram

Author: Widiarti, Yuning, Faumi, Fasa Imana, Chan, Albert P. C., Series Editor, Hong, Wei-Chiang, Series Editor, Mellal, Mohamed Arezki, Series Editor, Narayanan, Ramadas, Series Editor, Nguyen, Quang Ngoc, Series Editor, Ong, Hwai Chyuan, Series Editor, Sachsenmeier, Peter, Series Editor, Sun, Zaicheng, Series Editor, Ullah, Sharif, Series Editor, Wu, Junwei, Series Editor, Zhang, Wei, Series Editor, Al Rasyid, M. Udin Harun, editor, and Mufid, Mohammad Robihul, editor
Published: 2024
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20. Design of Biofouling Level Classification System Using Haar-Cascade Classifier And Local Binary Pattern Histogram

Author: Widiarti, Yuning, primary and Faumi, Fasa Imana, additional
Published: 2024
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21. Environmentally friendly slow-release urea fertilizer based on modified chitosan membrane

Author: Ariadi Lusiana, Retno, Widiarti Mariyono, Putri, Muhtar, Hasan, Edi Cahyaningrum, Sari, Abdillah Natsir, Taufik, and Efiyanti, Lisna
Published: 2024
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22. Retinoblastoma with and without Extraocular Tumor Extension: A Global Comparative Study of 3435 Patients

Author: Fabian, Ido Didi, Abdallah, Elhassan, Abdullahi, Shehu U., Abdulqader, Rula A., Abdulrahaman, Aminatu A., Abouelnaga, Sherif, Ademola-Popoola, Dupe S., Adio, Adedayo, Afifi, Mahmoud A., Afshar, Armin R., Aggarwal, Priyanka, Aghaji, Ada E., Ahmad, Alia, Akib, Marliyanti N.R., Akinsete, Adeseye M., Al Harby, Lamis, Al Mesfer, Saleh A., Al Ani, Mouroge H., Portabella, Silvia Alarcón, Al-Badri, Safaa A.F., Alcasabas, Ana Patricia A., Al-Dahmash, Saad A., Alejos, Amanda, Alemany-Rubio, Ernesto, Alfa Bio, Amadou I., Carreras, Yvania Alfonso, Al-Haddad, Christiane E., Al-Hussaini, Hamoud H.Y., Ali, Amany M., Alia, Donjeta B., Al-Jadiry, Mazin F., Al-Jumaly, Usama, Alkatan, Hind M., All-Eriksson, Charlotta, Al-Mafrachi, Ali A.R.M., Almeida, Argentino A., Alsawidi, Khalifa M., Al-Shaheen, Athar A.S.M., Al-Shammary, Entissar H., Amankwaa-Frempong, Doreen, Amiruddin, Primawita O., Armytasari, Inggar, Astbury, Nicholas J., Atalay, Hatice T., Ataseven, Eda, Atchaneeyasakul, La-ongsri, Atsiaya, Rose, Autrata, Rudolf, Balaguer, Julia, Balayeva, Ruhengiz, Barranco, Honorio, Bartoszek, Paulina, Bartuma, Katarina, Bascaran, Covadonga, Bechrakis, Nikolaos E., Popovic, Maja Beck, Begimkulova, Ainura S., Benmiloud, Sarra, Berete, Rokia C., Berry, Jesse L., Bhaduri, Anirban, Bhat, Sunil, Bhattacharyya, Arpita, Biewald, Eva M., Binkley, Elaine, Blum, Sharon, Bobrova, Nadia, Boldt, H. Culver, Bonanomi, Maria Teresa B.C., Bouda, Gabrielle C., Bouguila, Hédi, Brennan, Rachel C., Brichard, Bénédicte G., Buaboonnam, Jassada, Budiongo, Aléine, Burton, Matthew, Calderón-Sotelo, Patricia, Calle Jara, Doris A., Camuglia, Jayne E., Cano, Miriam R., Capra, Michael, Caspi, Shani, Cassoux, Nathalie, Castela, Guilherme, Castillo, Luis, Català-Mora, Jaume, Caviedes, Isabel, Chandramohan, Arthika, Chantada, Guillermo L., Chaudhry, Shabana, Chawla, Bhavna, Chen, Wensi, Chiwanga, Faraja S., Chuluunbat, Tsengelmaa, Cieslik, Krzysztof, Clark, Antony, Cockcroft, Ruellyn L., Comsa, Codruta, Correa Llano, Maria G., Corson, Timothy W., Couitchere, Line, Cowan-Lyn, Kristin E., Csóka, Monika, Dangboon, Wantanee, Das, Anirban, Das, Pranab, Das, Sima, Davanzo, Jacquelyn M., Davidson, Alan, De Francesco, Sonia, De Potter, Patrick, Delgado, Karina Q., Demirci, Hakan, Desjardins, Laurence, Diaz Coronado, Rosdali Y., Dimaras, Helen, Dodgshun, Andrew J., Donato Macedo, Carla R., Dragomir, Monica D., Du, Yi, Du Bruyn, Magritha, Du Plessis, Johannes P., Dudeja, Gagan, Eerme, Katrin, Eka Sutyawan, I Wayan, El Kettani, Asmaa, Elbahi, Amal M., Elder, James E., Elhaddad, Alaa M., Elhassan, Moawia M.A., Elzembely, Mahmoud M., Ericksen, Connor, Essuman, Vera A., Evina, Ted Grimbert A., Ezegwui, Ifeoma R., Fadoo, Zehra, Fandiño, Adriana C., Faranoush, Mohammad, Fasina, Oluyemi, Fernández, Delia D.P.G., Fernández-Teijeiro, Ana, Foster, Allen, Frenkel, Shahar, Fu, Ligia D., Fuentes-Alabi, Soad L., Garcia, Juan L., Aldana, David García, Garcia Pacheco, Henry N., Geel, Jennifer A., Ghassemi, Fariba, Girón, Ana V., Goenz, Marco A., Gold, Aaron S., Golberg, Hila, Gole, Glen A., Gomel, Nir, Gonzalez, Efren, Perez, Graciela Gonzalez, González-Rodríguez, Liudmira, Gorfine, Malka, Graells, Jaime, Gregersen, Pernille A., Grigorovski, Nathalia D.A.K., Guedenon, Koffi M., Gunasekera, D Sanjeeva, Gündüz, Ahmet K., Gupta, Himika, Gupta, Sanjiv, Gupta, Vineeta, Hadjistilianou, Theodora, Hamel, Patrick, Hamid, Syed A., Hamzah, Norhafizah, Hansen, Eric D., Harbour, J William, Hartnett, M. Elizabeth, Hasanreisoglu, Murat, Hassan, Sadiq, Hassan, Shadab, Hautz, Wojciech, Haydar, Huda A., Hederova, Stanislava, Hessissen, Laila, Lalaina, Hoby, Hongeng, Suradej, Hordofa, Diriba F., Hubbard, G. Baker, Hummlen, Marlies, Husakova, Kristina, Hussein Al-Janabi, Allawi N., Ibanga, Affiong A., Ida, Russo, Ilic, Vesna R., Islamov, Ziyavuddin, Jairaj, Vivekaraj, Janjua, Teyyeb A., Jeeva, Irfan, Ji, Xunda, Jo, Dong Hyun, Jones, Michael M., Amani Kabesha, Theophile B., Kabore, Rolande L., Kaliki, Swathi, Kalinaki, Abubakar, Kamsang, Pius, Kantar, Mehmet, Kapelushnik, Noa, Kardava, Tamar, Kebudi, Rejin, Keomisy, Jonny, Kepak, Tomas, Ketteler, Petra, Khan, Zohora J., Khaqan, Hussain A., Khetan, Vikas, Khodabande, Alireza, Khotenashvili, Zaza, Kim, Jonathan W., Kim, Jeong Hun, Kiratli, Hayyam, Kivelä, Tero T., Klett, Artur, Koç, Irem, Kosh Komba Palet, Jess Elio, Krivaitiene, Dalia, Kruger, Mariana, Kulvichit, Kittisak, Kuntorini, Mayasari W., Kyara, Alice, Lam, Geoffrey C., Larson, Scott A., Latinović, Slobodanka, Laurenti, Kelly D., Lavi, Yotam, Groznik, Alenka Lavric, Leverant, Amy A., Li, Cairui, Li, Kaijun, Limbu, Ben, Liu, Chun-Hsiu, Long, Quah Boon, López, Juan P., Lukamba, Robert M., Luna-Fineman, Sandra, Lutfi, Delfitri, Lysytsia, Lesia, Madgar, Shiran, Magrath, George N., Mahajan, Amita, Maitra, Puja, Maka, Erika, Makimbetov, Emil K., Maktabi, Azza M.Y., Maldonado, Carlos, Mallipatna, Ashwin, Manudhane, Rebecca, Manzhuova, Lyazat, Begue, Nieves Martín, Masud, Sidra, Matende, Ibrahim O., Mattosinho, Clarissa C.D.S., Matua, Marchelo, Mayet, Ismail, Mbumba, Freddy B., McKenzie, John D., Mehrvar, Azim, Mengesha, Aemero A., Menon, Vikas, Mercado, Gary John V.D.D., Mets, Marilyn B., Midena, Edoardo, Miller, Audra, Mishra, Divyansh K.C., Mndeme, Furahini G., Mohamedani, Ahmed A., Mohammad, Mona T., Moll, Annette C., Montero, Margarita M., Moreira, Claude, Mruthyunjaya, Prithvi, Msina, Mchikirwa S., Msukwa, Gerald, Mudaliar, Sangeeta S., Muhammad, Hassan, Muma, Kangwa I., Munier, Francis L., Murray, Timothy G., Musa, Kareem O., Mushtaq, Asma, Musika, Anne A., Mustak, Hamzah, Mustapha, Tajudeen, Muyen, Okwen M., Myezo, Khumo H., Naidu, Gita, Naidu, Natasha, Nair, Akshay Gopinathan, Natarajan, Sundaram, Naumenko, Larisa, Ndoye Roth, Paule Aïda, Nency, Yetty M., Neroev, Vladimir, Ng, Yvonne, Nikitovic, Marina, Nkanga, Elizabeth D., Nkumbe, Henry E., Numbi, Marcel N., Nummi, Kalle, Nuruddin, Murtuza, Nyaywa, Mutale, Nyirenda, Chinsisi, Obono-Obiang, Ghislaine, Oliver, Scott C.N., Ooporto, Joaquin, Ortega-Hernández, Miriam, Oscar, Alexander, Ossandon, Diego, Pagarra, Halimah, Paintsil, Vivian, Paiva, Luisa, Palanivelu, Mahesh Shanmugam, Papyan, Ruzanna, Parrozzani, Raffaele, Pascual Morales, Claudia R., Paton, Katherine E., Pe'er, Jacob, Calvo, Jesús Peralta, Perić, Sanja, Pham, Chau T.M., Philbert, Remezo, Plager, David A., Pochop, Pavel, Polania, Rodrigo A., Polyakov, Vladimir, Ponce, Jimena, Qadir, Ali O., Qayyum, Seema, Qian, Jiang, Rahman, Ardizal, Rajkarnikar, Purnima, Ramanjulu, Rajesh, Ramasubramanian, Aparna, Ramirez-Ortiz, Marco A., Randhawa, Jasmeen K., Raobela, Léa, Rashid, Riffat, Reddy, M. Ashwin, Renner, Lorna A., Reynders, David, Ribadu, Dahiru, Ritter-Sovinz, Petra, Rogowska, Anna, Rojanaporn, Duangnate, Romero, Livia, Roy, Soma R., Saab, Raya H., Saakyan, Svetlana, Sabhan, Ahmed H., Sagoo, Mandeep S., Said, Azza M.A., Saiju, Rohit, Salas, Beatriz, San Román Pacheco, Sonsoles, Sánchez, Gissela L., Sanchez Orozco, Alma Janeth, Sayalith, Phayvanh, Scanlan, Trish A., Schwab, Christoph, Sedaghat, Ahad, Seth, Rachna, Sgroi, Mariana, Shah, Ankoor S., Shakoor, Shawkat A., Sharma, Manoj K., Sherief, Sadik T., Shields, Carol L., Sia, David, Noorani Siddiqui, Sorath, Sidi cheikh, Sidi, Silva, Sónia, Singh, Arun D., Singh, Usha, Singha, Penny, Sitorus, Rita S., Skalet, Alison H., Soebagjo, Hendrian D., Sorochynska, Tetyana, Ssali, Grace, Stacey, Andrew W., Staffieri, Sandra E., Stahl, Erin D., Steinberg, David M., Stones, David K., Strahlendorf, Caron, Coleoni Suarez, Maria Estela, Sultana, Sadia, Sun, Xiantao, Superstein, Rosanne, Supriyadi, Eddy, Surukrattanaskul, Supawan, Suzuki, Shigenobu, Svojgr, Karel, Sylla, Fatoumata, Tamamyan, Gevorg, Tan, Deborah, Tandili, Alketa, Tang, Jing, Tarrillo Leiva, Fanny F., Tashvighi, Maryam, Tateshi, Bekim, Teh, Kok Hoi, Tehuteru, Edi S., Teixeira, Luiz F., Pompe, Manca Tekavcic, Thawaba, Abdullah Dahan M., Theophile, Tuyisabe, Toledano, Helen, Trang, Doan L., Traoré, Fousseyni, Tripathy, Devjyoti, Tuncer, Samuray, Tyau-Tyau, Harba, Umar, Ali B., Unal, Emel, Uner, Ogul E., Urbak, Steen F., Ushakova, Tatiana L., Usmanov, Rustam H., Valeina, Sandra, Valente, Paola, van Hoefen Wijsard, Milo, Vasquez Anchaya, Jacqueline Karina, Vaughan, Leon O., Veleva-Krasteva, Nevyana V., Verma, Nishant, Victor, Andi A., Viksnins, Maris, Villacís Chafla, Edwin G., Villegas, Victor M., Vishnevskia-Dai, Victoria, Waddell, Keith, Wali, Amina H., Wang, Yi-Zhuo, Wangtiraumnuay, Nutsuchar, Wetter, Julie A., Riono, Widiarti P., Wilson, Matthew W., Wime, Amelia D.C., Wiwatwongwana, Atchareeya, Wiwatwongwana, Damrong, Dod, Charlotte Wolley, Wong, Emily S., Wongwai, Phanthipha, Wu, Si-qi, Xiang, Daoman, Xiao, Yishuang, Xu, Bing, Xue, Kang, Yaghy, Antonio, Yam, Jason C., Yang, Huasheng, Yanga, Jenny M., Yaqub, Muhammad A., Yarovaya, Vera A., Yarovoy, Andrey A., Ye, Huijing, Yee, Roberto I., Yousef, Yacoub A., Yuliawati, Putu, López, Arturo M., Zein, Ekhtelbenina, Zhang, Yi, Zhilyaeva, Katsiaryna, Zia, Nida, Ziko, Othman A.O., Zondervan, Marcia, Schlüter, Sabrina, Bowman, Richard, and Vempuluru, Vijitha S.
Published: 2025
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23. Comparison between provisional and dual systematic stenting approach for left main bifurcation disease: A systematic review and meta-analysis

Author: Suryawan, I Gde Rurus, Saputra, Pandit Bagus Tri, Rurus, Made Edgard Surya Erlangga, Saputra, Mahendra Eko, Widiarti, Wynne, Multazam, Chaq El Chaq Zamzam, and Alkaff, Firas Farisi
Published: 2024
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24. Green synthesis of gaharu leaf extract-modified magnetite as an adsorbent for methyl orange textile dyes

Author: Sulistyaningsih, Triastuti, Sari, Dwi Atika, Widiarti, Nuni, Astuti, Widi, Wulandari, Rika, and Harjunowibowo, Dewanto
Published: 2024
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25. Retinoblastoma in Asia: Clinical Presentation and Treatment Outcomes in 2112 Patients from 33 Countries

Author: Kaliki, Swathi, Vempuluru, Vijitha S., Mohamed, Ashik, Abdulqader, Rula Ahmed, Aggarwal, Priyanka, Ahmad, Alia, Akib, Marliyanti Nur Rahmah, Al Mesfer, Saleh A., Al Ani, Mouroge Hashim, Al-Badri, Safaa A.Faraj, Angeles Alcasabas, Ana Patricia, Al-Dahmash, Saad A., Al-Haddad, Christiane, Yahya Al-Hussaini, Hamoud Hodeish, Al-Jadiry, Mazin Faisal, Al-Jumaily, Usama, Alkatan, Hind Manaa, Razzaq Mahmood Al-Mafrachi, Ali Abdul, Samad Majeed Al-Shaheen, Athar Abdul, Al-Shammary, Entissar Hadi, Amiruddin, Primawita Oktarima, Armytasari, Inggar, Astbury, Nicholas John, Atalay, Hatice Tuba, Ataseven, Eda, Atchaneeyasakul, La-ongsri, Balayeva, Ruhengiz, Bascaran, Covadonga, Begimkulova, Ainura Suranovna, Bhaduri, Anirban, Bhat, Sunil, Bhattacharyya, Arpita, Blum, Sharon, Bowman, Richard, Buaboonnam, Jassada, Burton, Matthew J., Caspi, Shani, Chaudhry, Shabana, Chawla, Bhavna, Chen, Wensi, Chuluunbat, Tsengelmaa, Dangboon, Wantanee, Das, Anirban, Das, Pranab, Das, Sima, Du, Yi, Dudeja, Gagan, Eka Sutyawan, I Wayan, Fadoo, Zehra, Faranoush, Mohammad, Foster, Allen, Frenkel, Shahar, Ghassemi, Fariba, Gomel, Nir, Gunasekera, D Sanjeeva, Gündüz, Ahmet K., Gupta, Himika, Gupta, Sanjiv, Gupta, Vineeta, Hamid, Syed Ahmer, Hamzah, Norhafizah, Hasanreisoglu, Murat, Hassan, Shadab, Haydar, Huda Awni, Hongeng, Suradej, Hussein Al-Janabi, Allawi Noor, Islamov, Ziyavuddin, Janjua, Teyyeb Azeem, Jeeva, Irfan, Ji, Xunda, Jo, Dong Hyun, Kantar, Mehmet, Kapelushnik, Noa, Kebudi, Rejin, Keomisy, Jonny, Khan, Zohora Jameela, Khaqan, Hussain Ahmed, Khetan, Vikas, Khodabande, Alireza, Kim, Jeong Hun, Kiratli, Hayyam, Koç, Irem, Kulvichit, Kittisak, Kuntorini, Mayasari Wahyu, Li, Cairui, Li, Kaijun, Limbu, Ben, Liu, ChunHsiu, Lutfi, Delfitri, Mahajan, Amita, Maitra, Puja, Makimbetov, Emil Kojoshovich, Maktabi, Azza M.Y., Manzhuova, Lyazat, Masud, Sidra, Mehrvar, Azim, Menon, Vikas, John V Mercado, Gary, Chandra Mishra, Divyansh Kailash, Mohammad, Mona Tayseer, Mudaliar, Sangeeta Sanjay, Mushtaq, Asma, Nair, Akshay Gopinathan, Natarajan, Sundaram, Nency, Yetty Movieta, Neroev, Vladimir, Nuruddin, Murtuza, Pagarra, Halimah, Palanivelu, Mahesh Shanmugam, Papyan, Ruzanna, Pe'er, Jacob, Polyakov, Vladimir, Qadir, Ali Omer, Qayyum, Seema, Qian, Jiang, Quah, BoonLong, Rahman, Ardizal, Rajkarnikar, Purnima, Ramanjulu, Rajesh, Rashid, Riffat, Rojanaporn, Duangnate, Roy, Soma Rani, Saab, Raya Hamad, Saakyan, Svetlana, Sabhan, Ahmed Hatem, Saiju, Rohit, Sayalith, Phayvanh, Sedaghat, Ahad, Seth, Rachna, Shakoor, Shawkat Ara, Sharma, Manoj Kumar, Siddiqui, Sorath Noorani, Singh, Usha, Singha, Penny, Sitorus, Rita S., Soebagjo, Hendrian D., Sultana, Sadia, Sun, Xiantao, Supriyadi, Eddy, Surukrattanaskul, Supawan, Suzuki, Shigenobu, Tan, Deborah, Tang, Jing, Tashvighi, Maryam, Teh, Kok Hoi, Tehuteru, Edi Setiawan, Thawaba, Abdullah Dahan M., Toledano, Helen, Le Trang, Doan, Tripathy, Devjyoti, Tuncer, Samuray, Unal, Emel, Ushakova, Tatiana L., Usmanov, Rustam, Verma, Nishant, Victor, Andi Arus, Vishnevskia-Dai, Victoria, Wang, Yi-Zhuo, Wangtiraumnuay, Nutsuchar, Riono, Widiarti Pandu, Wiwatwongwana, Atchareeya, Wiwatwongwana, Damrong, Wong, Emily S., Wongwai, Phanthipha, Wu, Si-qi, Xiang, Daoman, Xiao, Yishuang, Xu, Bing, Xue, Kang, Yam, Jason C., Yang, Huasheng, Yaqub, Muhammad Amer, Yarovaya, Vera A., Yarovoy, Andrey A., Ye, Huijing, Yousef, Yacoub Abdallah, Yuliawati, Putu, Zhang, Yi, Zia, Nida, Zondervan, Marcia, Fabian, Ido Didi, and Sthapit, Purnima Rajkarnikar
Published: 2024
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26. A Framework for Multi Institutional Collaboration for Pneumonia Screening by Means of Federated Learning.

Author: Agung Alfiansyah, Helena Widiarti, Vincentius Reynaldo, Wilsen Widjaja, and Laurent Bobelin
Published: 2023
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27. The Effect of Blended Learning Model with Realistic Mathematics Education (RME) Approach on Concept Understanding and Mathematics Problem Solving Ability of Students of Junior High School 11 Bengkulu City

Author: Widiarti, Yetti, Hanifah, Hanifah, Haji, Saleh, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Firdaus, M. Lutfi, editor, and Defianti, Aprina, editor
Published: 2023
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28. Wind-Generated Wave Simulation on Payangan Beach Utilizing DELFT3D

Author: Baresi, Enggar Setia, Wiyono, Retno Utami Agung, Widiarti, Wiwik Yunarni, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Kristiawan, Stefanus Adi, editor, Gan, Buntara S., editor, Shahin, Mohamed, editor, and Sharma, Akanshu, editor
Published: 2023
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29. Assessment of the Conditioning Factor for Flash Flood Susceptibility Potential Based on Bivariate Statistical Approach in the Wonoboyo Watershed in East Java, Indonesia

Author: Hidayah, Entin, Halik, Gusfan, Widiarti, Wiwik Yunarni, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Kristiawan, Stefanus Adi, editor, Gan, Buntara S., editor, Shahin, Mohamed, editor, and Sharma, Akanshu, editor
Published: 2023
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30. The roles of thyroidectomy in patients with amiodarone-induced thyrotoxicosis: A systematic review

Author: Widiarti, Wynne, Saputra, Pandit Bagus Tri, Mustofa, Ali, Meitavany, Estya Nadya, Oktaviono, Yudi Her, and Alkaff, Firas Farisi
Published: 2024
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31. The impact of cardiovascular drugs on hyperglycemia and diabetes: a review of ‘unspoken' side effects

Author: Widiarti, Wynne, Saputra, Pandit Bagus Tri, Savitri, Cornelia Ghea, Putranto, Johanes Nugroho Eko, and Alkaff, Firas Farisi
Published: 2024
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32. Appropriateness of Fluid Therapy in Cardiogenic Shock Management: A Systematic Review of Current Evidence

Author: Widiarti, Wynne, Multazam, Chaq El Chaq Z., Octaviana, Dinda S., Susilo, Hendri, Alsagaff, Mochamad Y., and Wungu, Citrawati D.K.
Published: 2024
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33. The Global Retinoblastoma Outcome Study: a prospective, cluster-based analysis of 4064 patients from 149 countries

Author: Fabian, Ido Didi, Abdallah, Elhassan, Abdullahi, Shehu U, Abdulqader, Rula A, Abdulrahaman, Aminatu A, Abouelnaga, Sherif, Ademola-Popoola, Dupe S, Adio, Adedayo, Afifi, Mahmoud A, Afshar, Armin R, Aggarwal, Priyanka, Aghaji, Ada E, Ahmad, Alia, Akib, Marliyanti NR, Akinsete, Adeseye, Al Harby, Lamis, Al Mesfer, Saleh, Al Ani, Mouroge H, Alarcón Portabella, Silvia, Al-Badri, Safaa AF, Alcasabas, Ana Patricia A, Al-Dahmash, Saad A, Alejos, Amanda, Alemany-Rubio, Ernesto, Alfa Bio, Amadou I, Alfonso Carreras, Yvania, Al-Haddad, Christiane E, Al-Hussaini, Hamoud HY, Ali, Amany M, Alia, Donjeta B, Al-Jadiry, Mazin F, Al-Jumaily, Usama, Alkatan, Hind M, All-Eriksson, Charlotta, Al-Mafrachi, Ali ARM, Almeida, Argentino A, Alsawidi, Khalifa M, Al-Shaheen, Athar ASM, Al-Shammary, Entissar H, Amankwaa-Frempong, Doreen, Amiruddin, Primawita O, Armytasari, Inggar, Astbury, Nicholas J, Atalay, Hatice T, Ataseven, Eda, Atchaneeyasakul, La-ongsri, Atsiaya, Rose, Autrata, Rudolf, Balaguer, Julia, Balayeva, Ruhengiz, Barranco, Honorio, Bartoszek, Paulina, Bartuma, Katarina, Bascaran, Covadonga, Bechrakis, Nikolaos E, Beck Popovic, Maja, Begimkulova, Ainura S, Benmiloud, Sarra, Berete, Rokia C, Berry, Jesse L, Bhaduri, Anirban, Bhat, Sunil, Bhattacharyya, Arpita, Biewald, Eva M, Binkley, Elaine, Blum, Sharon, Bobrova, Nadia, Boldt, H.C., Bonanomi, Maria Teresa BC, Bouda, Gabrielle C, Bouguila, Hédi, Brennan, Rachel C, Brichard, Bénédicte G, Buaboonnam, Jassada, Budiongo, Aléine, Burton, Matthew J, Calderón-Sotelo, Patricia, Calle Jara, Doris A, Camuglia, Jayne E, Cano, Miriam R, Capra, Michael, Caspi, Shani, Cassoux, Nathalie, Castela, Guilherme, Castillo, Luis, Català-Mora, Jaume, Cavieres, Isabel, Chandramohan, Arthika, Chantada, Guillermo L, Chaudhry, Shabana, Chawla, Bhavna, Chen, Wensi, Chiwanga, Faraja S, Chuluunbat, Tsengelmaa, Cieslik, Krzysztof, Clark, Antony, Cockcroft, Ruellyn L, Comsa, Codruta, Correa Llano, Maria G, Corson, Timothy W, Couitchere, Line, Cowan-Lyn, Kristin E, Csóka, Monika, Dangboon, Wantanee, Das, Anirban, Das, Pranab, Das, Sima, Davanzo, Jacquelyn M, Davidson, Alan, De Francesco, Sonia, De Potter, Patrick, Quintero D, Karina, Demirci, Hakan, Desjardins, Laurence, Díaz Coronado, Rosdali Y, Dimaras, Helen, Dodgshun, Andrew J, Donato Macedo, Carla R, Dragomir, Monica D, Du, Yi, Du Bruyn, Magritha, Du Plessis, Johannes, Dudeja, Gagan, Eerme, Katrin, Eka Sutyawan, I Wayan, El Kettani, Asmaa, Elbahi, Amal M, Elder, James E, Elhaddad, Alaa M, Elhassan, Moawia MA, Elzembely, Mahmoud M, Ericksen, Connor, Essuman, Vera A, Evina, Ted Grimbert A, Ezegwui, Ifeoma R, Fadoo, Zehra, Fandiño, Adriana C, Faranoush, Mohammad, Fasina, Oluyemi, Fernández, Delia DPG, Fernández-Teijeiro, Ana, Foster, Allen, Frenkel, Shahar, Fu, Ligia D, Fuentes-Alabi, Soad L, Garcia, Juan L, García Aldana, David, Garcia Pacheco, Henry N, Geel, Jennifer A, Ghassemi, Fariba, Girón, Ana V, Goenz, Marco A, Gold, Aaron S, Goldberg, Hila, Gole, Glen A, Gomel, Nir, Gonzalez, Efren, Gonzalez Perez, Graciela, González-Rodríguez, Liudmira, Gorfine, Malka, Graells, Jaime, Gregersen, Pernille A, Grigorovski, Nathalia DAK, Guedenon, Koffi M, Gunasekera, D Sanjeeva, Gündüz, Ahmet K, Gupta, Himika, Gupta, Sanjiv, Gupta, Vineeta, Hadjistilianou, Theodora, Hamel, Patrick, Hamid, Syed A, Hamzah, Norhafizah, Hansen, Eric D, Harbour, J William, Hartnett, M. Elizabeth, Hasanreisoglu, Murat, Muhammad, Hassan, Hassan, Sadiq, Hassan, Shadab, Hautz, Wojciech, Haydar, Huda, Hederova, Stanislava, Hessissen, Laila, Hongeng, Suradej, Hordofa, Diriba F, Hubbard, G. Baker, Hummelen, Marlies, Husakova, Kristina, Hussein Al-Janabi, Allawi N, Ibanga, Affiong, Ida, Russo, Ilic, Vesna R, Islamov, Ziyavuddin, Jairaj, Vivekaraj, Janjua, Teyyeb, Jeeva, Irfan, Ji, Xunda, Jo, Dong Hyun, Jones, Michael M, Kabesha Amani, Theophile B, Kabore, Rolande L, Kaliki, Swathi, Kalinaki, Abubakar, Kamsang, Pius, Kantar, Mehmet, Kapelushnik, Noa, Kardava, Tamar, Kebudi, Rejin, Keomisy, Jonny, Kepak, Tomas, Ketteler, Petra, Khan, Zohora J, Khaqan, Hussain A, Khetan, Vikas, Khodabande, Alireza, Khotenashvili, Zaza, Kim, Jonathan W, Kim, Jeong Hun, Kiratli, Hayyam, Kivela, Tero T., Klett, Artur, Koç, Irem, Kosh Komba Palet, Jess Elio, Krivaitiene, Dalia, Kruger, Mariana, Kulvichit, Kittisak, Kuntorini, Mayasari W, Kyara, Alice, Lam, Geoffrey C, Larson, Scott A, Latinović, Slobodanka, Laurenti, Kelly D, Lavy, Yotam, Lavric Groznik, Alenka, Leverant, Amy A, Li, Cairui, Li, Kaijun, Limbu, Ben, Liu, Chun-Hsiu, Quah, BoonLong, López, Juan P, Lukamba, Robert M, Luna-Fineman, Sandra, Lutfi, Delfitri, Lysytsia, Lesia, Madgar, Shiran, Magrath, George N, Mahajan, Amita, Maitra, Puja, Maka, Erika, Makimbetov, Emil K, Maktabi, Azza, Maldonado, Carlos, Mallipatna, Ashwin, Manudhane, Rebecca, Manzhuova, Lyazat, Martín-Begue, Nieves, Masud, Sidra, Matende, Ibrahim O, Mattosinho, Clarissa CDS, Matua, Marchelo, Mayet, Ismail, Mbumba, Freddy B, McKenzie, John D, Mehrvar, Azim, Mengesha, Aemero A, Menon, Vikas, Mercado, Gary John V, Mets, Marilyn B, Midena, Edoardo, Miller, Audra, Mishra, Divyansh KC, Mndeme, Furahini G, Mohamedani, Ahmed A, Mohammad, Mona T, Moll, Annette C, Montero, Margarita M, Moreira, Claude, Mruthyunjaya, Prithvi, Msina, Mchikirwa S, Msukwa, Gerald, Mudaliar, Sangeeta S, Muma, Kangwa I M, Munier, Francis L, Murray, Timothy G, Musa, Kareem O, Mushtaq, Asma, Musika, Anne A, Mustak, Hamzah, Mustapha, Tajudeen, Muyen, Okwen M, Myezo, Khumo H, Naidu, Gita, Naidu, Natasha, Nair, Akshay Gopinathan, Natarajan, Sundaram, Naumenko, Larisa, Ndoye Roth, Paule Aïda, Nency, Yetty M, Neroev, Vladimir, Ng, Yvonne, Nikitovic, Marina, Nkanga, Elizabeth D, Nkumbe, Henry E, Numbi, Marcel N, Nummi, Kalle, Nuruddin, Murtuza, Nyaywa, Mutale, Nyirenda, Chinsisi, Obono-Obiang, Ghislaine, Oliver, Scott CN, Oporto, Joaquin, Ortega-Hernández, Miriam, Oscar, Alexander H, Ossandon, Diego, Pagarra, Halimah, Paintsil, Vivian, Paiva, Luisa, Palanivelu, Mahesh Shanmugam, Papyan, Ruzanna, Parrozzani, Raffaele, Pascual Morales, Claudia R, Paton, Katherine E, Pe'er, Jacob, Peralta Calvo, Jesús, Perić, Sanja, Pham, Chau TM, Philbert, Remezo, Plager, David A, Pochop, Pavel, Polania, Rodrigo A., Polyakov, Vladimir, Ponce, Jimena, Qadir, Ali O, Qayyum, Seema, Qian, Jiang, Refaeli, David, Rahman, Ardizal, Rajkarnikar, Purnima, Ramanjulu, Rajesh, Ramasubramanian, Aparna, Ramirez-Ortiz, Marco A, Randhawa, Jasmeen K, Randrianarisoa, Hoby Lalaina, Raobela, Léa, Rashid, Riffat, Reddy, M.A., Renner, Lorna A, Reynders, David, Ribadu, Dahiru, Ritter-Sovinz, Petra, Rogowska, Anna, Rojanaporn, Duangnate, Romero, Livia, Roy, Soma R, Saab, Raya H, Saakyan, Svetlana, Sabhan, Ahmed H, Sagoo, Mandeep S, Said, Azza MA, Saiju, Rohit, Salas, Beatriz, San Román Pacheco, Sonsoles, Sánchez, Gissela L, Sanchez Orozco, Alma Janeth, Sayalith, Phayvanh, Scanlan, Trish A, Schlüter, Sabrina, Schwab, Christoph, Sedaghat, Ahad, Seth, Rachna, Sgroi, Mariana, Shah, Ankoor S, Shakoor, Shawkat A, Sharma, Manoj K, Sherief, Sadik T, Shields, Carol L, Sia, David, Siddiqui, Sorath Noorani, Sidi cheikh, Sidi, Silva, Sónia, Singh, Arun D, Singh, Usha, Singha, Penny, Sitorus, Rita S, Skalet, Alison H, Soebagjo, Hendrian D, Sorochynska, Tetyana, Ssali, Grace, Stacey, Andrew W, Staffieri, Sandra E, Stahl, Erin D, Steinberg, David M, Stones, David K, Strahlendorf, Caron, Suarez, Maria Estela Coleoni, Sultana, Sadia, Sun, Xiantao, Superstein, Rosanne, Supriyadi, Eddy, Surukrattanaskul, Supawan, Suzuki, Shigenobu, Svojgr, Karel, Sylla, Fatoumata, Tamamyan, Gevorg, Tan, Deborah, Tandili, Alketa, Tang, Jing, Tarrillo Leiva, Fanny F, Tashvighi, Maryam, Tateshi, Bekim, Teh, Kok Hoi, Tehuteru, Edi S, Teixeira, Luiz F, Tekavcic Pompe, Manca, Thawaba, Abdullah Dahan M, Theophile, Tuyisabe, Toledano, Helen, Trang, Doan L, Traoré, Fousseyni, Tripathy, Devjyoti, Tuncer, Samuray, Tyau-Tyau, Harba, Umar, Ali B, Unal, Emel, Uner, Ogul E, Urbak, Steen F, Ushakova, Tatiana L, Usmanov, Rustam H, Valeina, Sandra, Valente, Paola, van Hoefen Wijsard, Milo, Vasquez Anchaya, Jacqueline Karina, Vaughan, Leon O, Veleva-Krasteva, Nevyana V, Verma, Nishant, Victor, Andi A, Viksnins, Maris, Villacís Chafla, Edwin G, Villegas, Victor M, Vishnevskia-Dai, Victoria, Waddell, Keith, Wali, Amina H, Wang, Yi-Zhuo, Wangtiraumnuay, Nutsuchar, Wetter, Julie, Widiarti, Widiarti, Wilson, Matthew W, Wime, Amelia DC, Wiwatwongwana, Atchareeya, Wiwatwongwana, Damrong, Wolley Dod, Charlotte, Wong, Emily S, Wongwai, Phanthipha, Wu, Si-qi, Xiang, Daoman, Xiao, Yishuang, Xu, Bing, Xue, Kang, Yaghy, Antonio, Yam, Jason C, Yang, Huasheng, Yanga, Jenny M, Yaqub, Muhammad A, Yarovaya, Vera A, Yarovoy, Andrey A, Ye, Huijing, Yee, Roberto I, Yousef, Yacoub A, Yuliawati, Putu, Zapata López, Arturo M, Zein, Ekhtelbenina, Zhang, Yi, Zhilyaeva, Katsiaryna, Zia, Nida, Ziko, Othman AO, Zondervan, Marcia, and Bowman, Richard
Published: 2022
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34. Upgrading catalytic activity of NiO/CaO/MgO from natural limestone as catalysts for transesterification of coconut oil to biodiesel

Author: Widiarti, Nuni, Bahruji, Hasliza, Holilah, Holilah, Ni’mah, Yatim Lailun, Ediati, Ratna, Santoso, Eko, Jalil, Aishah Abdul, Hamid, Abdul, and Prasetyoko, Didik
Published: 2023
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35. Meningkatkan kemandirian belajar dengan e-modul interaktif genially / DEFITA WIDIARTI

Author: Widiarti, Defita Widiarti and Widiarti, Defita Widiarti
Abstract: Kemajuan teknologi semakin canggih di bidang pendidikan seperti e-modul interaktif sangat berdampak pada kualitas pendidikan pada kualitas pembelajaran di kelas.Tujuan dikembangkannya e-modul berbentuan genially yaitu untuk menghasilkan e-modul interaktif yang telah melalui validasi ahli materi dan ahli e-modul serta mengetahui perbedaan kemandirian belajar peserta didik kelas eksperimen dan kelas control. Metode penelitian yang digunakan adalah metode R amp D menurut Born and Gall yang terdiri dari 10 tahapan yang dimodifikasi oleh peneliti menjadi 9 tahapan. Peserta didik kelas XI SMK ahli e-modul dan ahli materi menjadi subyek penelitian. Setelah e-modul diterapkan pada peserta didik kemandirian peserta didik meningkat. Hal ini dibuktikan adanya perbedaan kemandirian belajar pada kelas eksperimen dan kelas kontrol pada elemen Pengelolaan Sarana dan Prasarana. Data yang diperoleh adalah data kualitatif dan data kuantitatif. Data diolah menggunakan deskriptif persentase. Hasil uji kelayakan ahli e-modul dan ahli materi serta uji coba kelompok kecil menyatakan bahwa penyajian dan tampilan konten sangat layak persentase nilai kategori tinggi. Hasil tersebut menunjukkan bahwa e-modul elemen Pengelolaan Sarana dan Prasarana berguna untuk meningkakan kemandirian peserta didik pada elemen Pengelolaan Sarana dan Prasarana layak digunakan sebagai bahan ajar
Published: 2024

36. The Effect of Air Injection Flowrate on Nitrate Synthesis with The Addition of Fe2+ Ions Using Plasma Electrolysis.

Author: Harianingsih, Harianingsih, Sulistyawan, Vera Noviana, Kusumaningrum, Maharani, Widiarti, Nuni, Pangestu, Indra Sakti, Putra, Muhammad Rizky Fahrizal, Ritmadanti, Afifah, and Kurniawan, Tonni Agustiono
Published: 2024
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37. Assessment of the Conditioning Factor for Flash Flood Susceptibility Potential Based on Bivariate Statistical Approach in the Wonoboyo Watershed in East Java, Indonesia

Author: Hidayah, Entin, primary, Halik, Gusfan, additional, and Widiarti, Wiwik Yunarni, additional
Published: 2022
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38. Wind-Generated Wave Simulation on Payangan Beach Utilizing DELFT3D

Author: Baresi, Enggar Setia, primary, Wiyono, Retno Utami Agung, additional, and Widiarti, Wiwik Yunarni, additional
Published: 2022
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39. The Effect of Port Growth on the Safety Index in Madura Strait.

Author: Hardhita, DW, Asmara, IPS, and Widiarti, Y
Published: 2024
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40. The Relationship Between Coping and Stress Levels in Students from The Class of 2020 at The Faculty of Medicine, Palangka Raya University, During Their Thesis Preparation.

Author: Gloria, Netanya, Martani, Natalia Sri, Arifin, Syamsul, Jelita, Helena, and Widiarti, Astri
Subjects: PERCEIVED Stress Scale, STRESS management, OVERPRESSURE (Education), INTERVAL analysis, STATISTICAL sampling
Abstract: Introduction: Academic stress is prevalent among final-year students, with thesis preparation being a significant source of this stress. Coping are essential as they effectively represent the body’s conscious adaptive responses to reduce stress through self-adaptation. This research determines the relationship between coping and stress levels in students from the class of 2020 at the Faculty of Medicine, Palangka Raya University, during their thesis preparation. Methods: The study employs a quantitative analytical observational design with a cross-sectional approach. Simple random sampling was utilized for participant selection. The research instruments comprised coping questionnaires and the Perceived Stress Scale (PSS-10). Data were analyzed using Charles Spearman’s correlation analysis with a confidence interval of 95%. Results: Out of all 96 respondents, 49 individuals (51%) had good coping skills, and 80 individuals (83.3%) experienced moderate stress levels. Notably, among the 49 participants exhibiting good coping, a majority (42 individuals or 85.71%) experienced moderate stress levels. The Charles Spearman test findings revealed a significant value of 0,013 (p < 0.05) with a weak correlation and the opposite direction (r = -0.252). Conclusion: There is a significant relationship between coping and stress levels in students from the class of 2020 at the Faculty of Medicine, Palangka Raya University, during their thesis preparation. [ABSTRACT FROM AUTHOR]
Published: 2024
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41. Enhancing the Transliteration of Words written in Javanese Script through Augmented Reality.

Author: Widiarti, Anastasia Rita and Adji, Fransisca Tjandrasih
Subjects: LIFE cycles (Biology), AUGMENTED reality, DEPERSONALIZATION, SATISFACTION, TRANSLITERATION
Abstract: In the Special Region of Yogyakarta Province and Central Java Province, where most of the population is Javanese, the use of Javanese script in daily life is increasingly replaced by Latin script, endangering the further loss of the Javanese identity. This research describes the development of marker-based Augmented Reality (AR) technology to create a Javanese word-reading application. The markers in printed Javanese characters are taken from a Javanese script manuscript entitled Hamong Tani. The markers can be arranged in various ways by the user to form words, with the maximum number of markers that make up words being 5. Whenever the camera is aimed at a row of markers that make up words, additional information will come out as translation results written in Latin. The results of testing the application called Jawalens, which was developed deploying the Multimedia Development Life Cycle (MDLC) method, on 38 users show that it has high levels of usefulness, satisfaction, and ease of use. It is hoped that Jawalens can help the younger generation re-learn and read Javanese scripts. Apart from that, the development method described in this paper is expected to inspire the younger generation in other regions or countries to develop similar applications, and thus help preserve their ancient scripts. [ABSTRACT FROM AUTHOR]
Published: 2024
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42. Privacy-preserving collaboration in healthcare systems via federated learning.

Author: Alfiansyah, Agung and Widiarti, Helena
Subjects: *COMPUTER-aided diagnosis, *FEDERATED learning, *PNEUMONIA-related mortality, *MEDICAL imaging systems, *ARTIFICIAL intelligence
Abstract: This research initiative aims to reduce pneumonia-related mortality rates, particularly among children in remote areas. The proposed solution involves creating an AI-based automatic screening system that analyzes X-ray images of patients and stores image data across hospitals in a distributed manner. The main goal is achieved through a collaborative approach, utilizing Federated Learning to establish a platform for hospital cooperation. Each participating hospital contributes to diagnostic improvement by developing local models from their datasets. These local models are then sent to a central server, where they are combined and refined to form a comprehensive global model. This process ensures unbiased detection by considering data from various sources. Patient data security is prioritized, as the central server only stores local models and not sensitive patient information. Additionally, the project introduces an innovative system for managing medical image data. This system not only archives, anonymizes, and secures image data but also curates a dataset necessary for training Computer Assisted Diagnosis systems. This work aims to push the boundaries of machine learning, particularly in healthcare, with a strong focus on patient privacy and anonymity. [ABSTRACT FROM AUTHOR]
Published: 2024
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43. Generalized space-time autoregressive (GSTAR) modeling with seemingly unrelated regression (SUR) for forecasting inflation data in five cities on the island of Sumatra.

Author: Suciati, Indah, Widiarti, Usman, Mustofa, Warsono, and Wamiliana
Subjects: *RUSSIAN invasion of Ukraine, 2022-, *GENERALIZED spaces, *INFLATION forecasting, *CITIES & towns, *TIME series analysis
Abstract: The Covid-19 pandemic and Russian invasion of Ukraine made food and energy prices in the world soar. This price spike has triggered inflation in various countries, such as Indonesia. Currently, the most developed forecasting method is the time series. The development of a multivariate time series, apart from looking at the time element, also involves an element of location. One model that involves time and location is the Generalized Space Time Autoregressive (GSTAR) model. The GSTAR model is a development of the Space Time Autoregressive (STAR) model which assumes that the location element is heterogeneous. The purpose of this study was to obtain the GSTAR model using Seemingly Unrelated Regression (SUR) on inflation data in five cities on the island of Sumatra. The methods used in this study are, 1) perform descriptive analysis, 2) perform stationarity test, 3) identify the GSTAR model, 4) calculate the location weight matrix, and 5) calculate parameter estimates for the GSTAR model using the SUR method. In this study, it is found that the inflation model for five cities on the island of Sumatra at time t is correlated with inflation data at the previous time and is influenced by inflation data from other cities. [ABSTRACT FROM AUTHOR]
Published: 2024
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44. The BVAR model approach in predicting the JCI index, USD-IDR exchange rate, and EUR-IDR exchange rate during the COVID-19 pandemic.

Author: Juanda, Usman, Mustofa, Kurniasari, Dian, Widiarti, Amanto, and Warsono
Subjects: COVID-19 pandemic, STANDARD deviations, FOREIGN exchange rates, AUTOREGRESSIVE models, STATISTICS
Abstract: The main purpose of this article is to explore the evidence that the Bayesian Vector Autoregressive Model (BVAR) is a good forecasting model in predicting the value of the JCI index, the USD-IDR exchange rate, and the EUR-IDR exchange rate during the COVID-19 pandemic which can be seen from the forecasting accuracy value. We can see the accuracy of forecasting from the value of Mean Error (ME) to see the unfamiliarity of forecasting, Root Mean Square Error (RMSE) to see the diversity of forecasting. The BVAR model uses the Bayesian method in estimating the parameters of the vector autoregressive (VAR) model. This article uses Minnesota priors in assessing the BVAR model. The variables used are Y1 for the JCI, Y2 for the USD-IDR exchange rate, and Y3 for the EUR-IDR exchange rate. The methodology carried out, 1) Presenting descriptive statistical data in the form of boxplots, 2) seeing the stationarity of the data, looking at the ACF, PACF and ADF diagrams, if there are variables that are not stationary then differencing will be carried out, 3) Identifying the BVAR model, 4) Seeing the accuracy of forecasting BVAR against the JCI index, USD-IDR exchange rate and EUR-IDR exchange rate with ME, and RMSE indicators. The BVAR model is proven to be a good forecasting model (unbiased and small variance) in predicting the value of the JCI index, USD-IDR exchange rate, and EUR-IDR exchange rate with an ME value of 7.79007 and RMSE of 52.70694. [ABSTRACT FROM AUTHOR]
Published: 2024
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45. PENGENALAN SOFTWARE MANAJEMEN PRODUKSI PEMBANGUNAN KAPAL IKAN TRADISIONAL PADA SERIKAT PEKERJA SEKAWAN GROUP DI LAMONGAN

Author: Rustini, Irma, primary, Arumsari, Nurvita, additional, Widiana, Dika Rahayu, additional, Praharsi, Yugowati, additional, and Widiarti, Yuning, additional
Published: 2024
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46. PENGARUH KUALITAS, HARGA DAN PROMOSI TERHADAP KEPUTUSAN PEMBELIAN

Author: Widiarti, Aniek, primary, Syamiya, Estu Niana, additional, and Supriatin, Udoh, additional
Published: 2024
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47. KUALITAS LAYANAN DAN HARGA SEBAGAI PENENTU KEPUTUSAN PEMBELIAN MINUMAN KOPI

Author: Khusaini, Khusaini, primary, Mawaddah, Siti Nurul, additional, and Widiarti, Aniek, additional
Published: 2024
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48. The effect of calcination on natural calcareous bentonite for Mn and Fe adsorption in aqueous solution

Author: Prastistho, Widyawanto, primary and Wahyuning Widiarti, Ika, additional
Published: 2024
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49. Analysis of Consumer Satisfaction with Digital Marketing and Service Quality

Author: Suyaman, Dede Jajang, primary, Cunayah, Cucun, additional, Widiarti, Widiarti, additional, and Nurhanansyah, Moch Fachrizal, additional
Published: 2024
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50. Modeling and Analysis Data Production of Oil, and Oil and Gas in Indonesia by Using Threshold Vector Error Correction Model

Author: Widiarti, Widiarti, primary, Usman, Mustofa, additional, Putri, Almira Rizka, additional, and Russel, Edwin, additional
Published: 2024
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