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1. Faktor internal dan ekternal apakah berkaitan dengan minat siswa dalam pembelajaran bola voli?

Author

Raihan M Muller Markaya, Irfan Zinat Achmad, and Muhammad Mury Syafei

Subjects
internal, ekternal, minat, bolavoli, Sports, GV557-1198.995, Sports medicine, RC1200-1245
Abstract

Masalah: Rendahnya minat belajar bola voli pada siswa merupakan permasalahan utama dalam penelitian ini. Tujuan: Penelitian ini bertujuan untuk mengungkap faktor-faktor yang berkaitan dengan minat siswa dalam belajar bola voli. Metode: Dalam penelitian ini mengadaptasi jenis survey. 80 siswa yang menjadi sampel dalam penelitian ini berasal dari MAN 1 Kota Bekasi. Instrumen dalam penelitian ini menggunakan angket minat. Semua data hasil pengisian angket di analisis menggunakan MS. Excel 2013 untuk mencari frekuensi dan persentase dari setiap indikator minat. Hasil: Temuan penelitian ini menunjukan bahwa indikator daya tarik sebanyak 48 siswa menyatakan sangat setuju, 23 siswa setuju, 5 siswa cukup setuju, 2 siswa kurang setuju dan 1 siswa tidak setuju dengan persentase 88%. Indikator perhatian sebanyak 26 siswa menyatakan sangat setuju, 40 siswa setuju, 9 siswa cukup setuju, 4 siswa kurang setuju dan 1 siswa tidak setuju dengan persentase 81%. Indikator partisipasi sebanyak 26 siswa menyatakan sangat setuju, 37 siswa setuju, 10 siswa cukup setuju, 5 siswa kurang setuju dan 2 siswa tidak setuju dengan persentase 80%. Indikator dukungan keluarga sebanyak 39 siswa menyatakan sangat setuju, 28 siswa setuju, 8 siswa cukup setuju, 3 siswa kurang setuju dan 2 siswa tidak setuju dengan persentase 84%. Indikator fasilitas sebanyak 50 siswa menyatakan sangat setuju, 25 siswa setuju, 4 siswa cukup setuju, 1 siswa kurang setuju dan 0 siswa tidak setuju dengan persentase 91%.. Kesimpulan: Kesimpulan dalam penelitian ini adalah bahwa faktor-faktor yang berkaitan erat dengan tingkat minat siswa dalam mengikuti proses pembelajaran bola voli yaitu factor internal dan ekternal yang meliputi daya tarik pembelajaran, perhatian/kosentrasi, partisipasi, dukungan keluarga dan fasilitas belajar

Published
2023
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2. Spinal subarachnoid and subdural hematoma presenting as a Brown-Séquard-like myelopathy following minor trauma in a patient on dabigatran etexilate

Author

Allen R. Wolfe, MD, MPH, Raihan M. Faroqui, BA, George A. Visvikis, MD, Michael T. Mantello, MD, Allan B. Perel, MD, and Sanjit O. Tewari, MD

Subjects
Dabigatran etexilate, Hematoma, Brown-Séquard syndrome, Extraaxial, Trauma, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Dabigatran etexilate is a relatively new anticoagulant from the class of direct thrombin inhibitors which is administered orally and does not require routine blood work monitoring. Dabigatran may be attractive to both clinicians and patients because of both its convenience and efficacy; however, clinical complications are still being elucidated. Here, we present a previously unreported case of spinal subarachnoid and subdural hematoma presenting as a Brown-Séquard-like myelopathy in a patient after minor trauma in the setting of Dabigatran anticoagulation.

Published
2017
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3. Unleashing Modified Deep Learning Models in Efficient COVID-19 Detection

Author

Aminul Islam, Md., Shuvo, Shabbir Ahmed, Rony, Mohammad Abu Tareq, Raihan, M., Abu Sufian, Md., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Mahmud, Mufti, editor, Kaiser, M. Shamim, editor, Bandyopadhyay, Anirban, editor, Ray, Kanad, editor, and Al Mamun, Shamim, editor

Published
2025
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4. Unleashing Modified Deep Learning Models in Efficient COVID19 Detection

Author

Islam, Md Aminul, Shuvo, Shabbir Ahmed, Rony, Mohammad Abu Tareq, Raihan, M, and Sufian, Md Abu

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing
Abstract

The COVID19 pandemic, a unique and devastating respiratory disease outbreak, has affected global populations as the disease spreads rapidly. Recent Deep Learning breakthroughs may improve COVID19 prediction and forecasting as a tool of precise and fast detection, however, current methods are still being examined to achieve higher accuracy and precision. This study analyzed the collection contained 8055 CT image samples, 5427 of which were COVID cases and 2628 non COVID. The 9544 Xray samples included 4044 COVID patients and 5500 non COVID cases. The most accurate models are MobileNet V3 (97.872 percent), DenseNet201 (97.567 percent), and GoogleNet Inception V1 (97.643 percent). High accuracy indicates that these models can make many accurate predictions, as well as others, are also high for MobileNetV3 and DenseNet201. An extensive evaluation using accuracy, precision, and recall allows a comprehensive comparison to improve predictive models by combining loss optimization with scalable batch normalization in this study. Our analysis shows that these tactics improve model performance and resilience for advancing COVID19 prediction and detection and shows how Deep Learning can improve disease handling. The methods we suggest would strengthen healthcare systems, policymakers, and researchers to make educated decisions to reduce COVID19 and other contagious diseases. CCS CONCEPTS Covid,Deep Learning, Image Processing KEYWORDS Covid, Deep Learning, DenseNet201, MobileNet, ResNet, DenseNet, GoogleNet, Image Processing, Disease Detection.

Published
2023

5. Spontaneous subcutaneous emphysema of the scalp following hair coloring/treatment

Author

Sanjit O. Tewari, MD, Raihan M. Faroqui, BA, Nicholas Fuca, MD, Mansoor Khan, MD, MHA, and Michael T. Mantello, MD

Subjects
Subcutaneous emphysema, hair coloring, hair treatment, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Subcutaneous emphysema of the scalp is a process often attributed to secondary factors such as trauma, infection, or a myriad of iatrogenic etiologies. Here, we are presenting a case report of an adult patient with spontaneous subcutaneous emphysema of the scalp following a hair coloring/treatment. We performed an extensive review of literature on this topic, however, could not find a single case with similar presentation of subcutaneous emphysema. This case demonstrates an unreported etiology for this diagnosis and is thus being reported for its uniqueness and to raise clinical awareness.

Published
2017
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7. AutoCl : A Visual Interactive System for Automatic Deep Learning Classifier Recommendation Based on Models Performance

Author

Ahmed, Fuad, Ferdows, Rubayea, Islam, Md Rafiqul, and Kamal, Abu Raihan M.

Subjects
Computer Science - Machine Learning
Abstract

Nowadays, deep learning (DL) models being increasingly applied to various fields, people without technical expertise and domain knowledge struggle to find an appropriate model for their task. In this paper, we introduce AutoCl a visual interactive recommender system aimed at helping non-experts to adopt an appropriate DL classifier. Our system enables users to compare the performance and behavior of multiple classifiers trained with various hyperparameter setups as well as automatically recommends a best classifier with appropriate hyperparameter. We compare features of AutoCl against several recent AutoML systems and show that it helps non-experts better in choosing DL classifier. Finally, we demonstrate use cases for image classification using publicly available dataset to show the capability of our system., Comment: This research paper has accepted and presented in The 28th International Workshop on Frontiers of Computer Vision (IW-FCV). IW-FCV held fully virtual on February 21-22, 2022. See https://sites.google.com/view/iwfcv2022 for details

Published
2022

10. Lung Cancer Detection from Histopathological Images Using Deep Learning

Author

Mohalder, Rahul Deb, Hossain, Khandkar Asif, Sarkar, Juliet Polok, Paul, Laboni, Raihan, M., Talukder, Kamrul Hasan, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Satu, Md. Shahriare, editor, Moni, Mohammad Ali, editor, Kaiser, M. Shamim, editor, and Arefin, Mohammad Shamsul, editor

Published
2023
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14. Fake News Detection of COVID-19 Using Machine Learning Techniques

Author

Ghosh, Promila, Raihan, M., Hassan, Md. Mehedi, Akter, Laboni, Zaman, Sadika, Awal, Md. Abdul, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Vasant, Pandian, editor, Zelinka, Ivan, editor, and Weber, Gerhard-Wilhelm, editor

Published
2022
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15. Paddy Disease Prediction Using Convolutional Neural Network

Author

Hossain, Khandkar Asif, Raihan, M., Biswas, Avijit, Sarkar, Juliet Polok, Sultana, Suriya, Sana, Kajal, Sarder, Keya, Majumder, Nilanjana, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Vasant, Pandian, editor, Zelinka, Ivan, editor, and Weber, Gerhard-Wilhelm, editor

Published
2022
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16. Paddy Price Prediction in the South-Western Region of Bangladesh

Author

Sarkar, Juliet Polok, Raihan, M., Biswas, Avijit, Hossain, Khandkar Asif, Sarder, Keya, Majumder, Nilanjana, Sultana, Suriya, Sana, Kajal, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Vasant, Pandian, editor, Zelinka, Ivan, editor, and Weber, Gerhard-Wilhelm, editor

Published
2022
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17. Human Depression Prediction Using Association Rule Mining Technique

Author

Biilah, Md. Al-Mamun, Raihan, M., Akter, Tamanna, Alvi, Nasif, Bristy, Nusrat Jahan, Rehana, Hasin, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Gupta, Deepak, editor, Bhattacharyya, Siddhartha, editor, Hassanien, Aboul Ella, editor, Anand, Sameer, editor, and Jaiswal, Ajay, editor

Published
2022
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18. Breast Cancer Risk Prediction Using Different Clustering Techniques

Author

Akter, Laboni, Raihan, M., Raihan, Md. Mohsin Sarker, Ghosh, Mounita, Alvi, Nasif, Ferdib-Al-Islam, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Gupta, Deepak, editor, Bhattacharyya, Siddhartha, editor, Hassanien, Aboul Ella, editor, Anand, Sameer, editor, and Jaiswal, Ajay, editor

Published
2022
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19. Utilization of Machine Learning Algorithms for Thyroid Disease Prediction

Author

Shahajalal, Md., Rahman, Md. Masudur, Pranto, Sk. Arifuzzaman, Ema, Romana Rahman, Islam, Tajul, Raihan, M., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Gupta, Deepak, editor, Bhattacharyya, Siddhartha, editor, Hassanien, Aboul Ella, editor, Anand, Sameer, editor, and Jaiswal, Ajay, editor

Published
2022
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21. An Empirical Study on Diabetes Mellitus Prediction Using Apriori Algorithm

Author

Tanvir Islam, Md., Raihan, M., Farzana, Fahmida, Ghosh, Promila, Ahmed Shaj, Shakil, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Gupta, Deepak, editor, Khanna, Ashish, editor, Bhattacharyya, Siddhartha, editor, Hassanien, Aboul Ella, editor, Anand, Sameer, editor, and Jaiswal, Ajay, editor

Published
2021
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27. Diabetes Mellitus Prediction Using Ensemble Machine Learning Techniques

Author

Islam, Md. Tanvir, Raihan, M., Akash, Sheikh Raihan Islam, Farzana, Fahmida, Aktar, Nasrin, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Barbosa, Simone Diniz Junqueira, Founding Editor, Saha, Ashim, editor, Kar, Nirmalya, editor, and Deb, Suman, editor

Published
2020
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37. Addressing the effectiveness of health literacy programs within the Gulf Corporation Council: an integrative review.

Author

Johnson, J, Mohamed, H, Lowe, T, Khraim, F, Wolsey, C, Haque, S, Al-Farsi, A, Schnurman, D, Chowdhury, N, Raihan, M M H, and Turin, T C

Subjects
HEALTH literacy, HEALTH self-care, MEDICAL care use, HEALTH services accessibility, COST control, FAMILY health, HUMAN services programs, EVALUATION of human services programs, SOCIOECONOMIC factors, COMMUNITIES, CONCEPTUAL structures, HEALTH promotion, PUBLIC health, SOCIODEMOGRAPHIC factors, QUALITY assurance, MEDICAL care costs
Abstract

Health literacy is an increasingly required need to help individuals, families and communities manage their health and health conditions. It is linked with better self-adherence to treatments, use of resources, access to care and overall reduced costs in healthcare. In the Gulf Cooperation Council (GCC), which comprises Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates, various health literacy programs are implemented across states to address people's unique and complex healthcare needs. This article aims to examine the current literature and assess the factors that influence the outcomes of health literacy programs within the GCC. An integrative review methodology has been conducted to pursue a comprehensive understanding of health literacy interventions in the GCC. This investigative approach was shaped by Whittemore and Knafl's framework (2005), which includes problem identification, literature search, data evaluation, data analysis and presentation. The literature on the effectiveness of health literacy interventions and the factors that shape them are notably limited worldwide and within the GCC region. This integrative review addresses this knowledge gap and highlights the significance of key themes such as sessions, evaluation and improvement in shaping health literacy outcomes within the GCC region. Through this integrative review, the three main themes of sessions, evaluation and improvement were identified as influencing the outcomes of health literacy programs within the GCC. [ABSTRACT FROM AUTHOR]

Published
2024
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38. Psychological Well-Being Reviewed By The Work Complacency Of The Employees Of Pt. Abs.

Author

Hartini, Sri, Tania, Angelyn, Simwira, Chaterine, Raihan, M. Hafizh, El Akmal, Mukhaira, and Rezeki, Sabrini Mentari

Subjects
PSYCHOLOGICAL well-being, JOB satisfaction, PEARSON correlation (Statistics), WELL-being, JUDGMENT sampling
Abstract

The study is held in PT. Andalan Bintang Sampali working environment. The objective is to obtain the bond among the job satisfaction with psychological well-being of PT. Andalan Bintang Sampali’s employees. Population and sample on this research is: 102 (a hundred and two) employees of PT. Andalan Bintang Sampali. The method of Purposive Sampling is being used as the technique to collect samples. The technique of gathering data is by disseminate the questions-form to those samples. Analysis technique that is being carried out in this study/research is the Correlational Pearson Product Moment technique.The results of the research found a correlation between work satisfaction and psychological well-being with the correlation coefficient F = 0.947 as well as p = 0.000 (p<0.01). The assumption test composed of normality test, linearity trial, correlation check, descriptive test, as well as effective contribution test. The data was outlined with SPSS 27 for Windows by using Correlation Pearson Product Moment technique. Research shows that the effective contribution shows that 94.7 percent occured within job satisfaction and psychologial wellbeing, while the rest 5.3 percent lie on other factors that weren’t being researched. [ABSTRACT FROM AUTHOR]

Published
2024
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