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The purpose of this study was to determine the optimal portfolio in the telecommunications sector listed on the Indonesia Stock Exchange based on the Jakarta Composite Index for the period January 2018–December 2020 using the Single Index Model. This type of research is an applied research. This type of research is applied research with secondary data obtained from the Indonesia Stock Exchange, Yahoo Finance, and Bank Indonesia. The number of samples taken is 5 stocks, namely TLKM, ISAT, EXCL, BTEL, and FREN. Based on the results of the analysis of the 5 stocks that are members of the JCI, the combination of 2 stocks that make up the optimal portfolio, namely ISAT and FREN, produces an expected return of 5.08% with a risk of 8.02%.

Ordinary kriging is the most widely used kriging method. It serves to estimate a value at a point of a region for which a variogram is known, using data in the neighborhood of the estimation location. Ordinary kriging can also be used to estimate a block value. With local second-order stationarity, ordinary kriging implicitly evaluates the mean in a moving neighborhood. To see this, first a kriging estimate of the local mean is set up, then a simple kriging estimator using this kriged mean is examined. The objective of this study was to determine the pattern of diarrheal disease spread in Bogor Regency. The method according to the purpose of this research is Ordinary Kriging. To know the distribution of diarrhea disease in Bogor Regency by looking at the result of countour plot. Based on the countour plot, the area that has the highest number of diarrhea sufferers around Barekah and Bojonggenteng villages is marked with White contour color with the range of diarrhea sufferer is 40 - 43 people. Areas with the highest number of diarrheal diseases indicate that the area has a relationship with the number of diarrheal diseases in the surrounding area. Therefore, the area needs to be prioritized in improving water sanitation, counseling to the community and improving health services.

The purpose of this study is to determine the appropriate forecasting method for predicting rainfall in Makassar City in 2022. This research is based on the problems that are often experienced by the people of Makassar City, namely the occurrence of flooding which results in traffic jams due to high x rainfall which continuously occurs. for several days in a row. With this research, people can see the prediction of rainfall and anticipate flooding in Makassar City. The results of the Makassar city rainfall data plot experience increases and decreases (fluctuations), which tend to repeat every year. This shows that Makassar City's rainfall contains seasonal factors. Therefore the method used is one-parameter Brown triple exponential smoothing, three-parameter Holt-Winters additive and Holt-Winters multiplicative. The forecasting results show that the correct method to use is the Holt-Winters multiplicative method with a parameter value of a=0.001 β=0.15 γ=0.002 which produces a minimum value of MAPE = 1.18 MAD = 136.23 compared to the Brown and Holt-Winters methods additive. Forecasting results using the Holt-Winters multiplicative method show that the highest rainfall occurs from December to April 2022.

The aims of thi study is to know the effect of review video making on problem based learning to spatial ability. This research is a quasy experimental research using posttest only control design. The experimental class applied video review on problem-based learning model and the control class did not do video review but only applied problem-based learning model. The population in this study amounted to 49 people and the research sample was 40 people. The sampling technique used in determining the research sample was purposive sampling technique. The research instrument used an essay test which was prepared based on indicators of spatial ability consisting of spatial perception, mental rotation, and spatial visualization. Data analysis techniques include descriptive analysis and inferential analysis. Descriptive data analysis describes the comparison of spatial ability scores of experimental and control classes while inferential analysis is used to test the hypothesis. Descriptive analysis of spatial abilities obtained the average value of the experimental class and control class is 90.50 and 59.50, The results of the spatial ability analysis test using the Mann-Whitney test showed a significance value

This study aims to predict a student’s graduation on time (GOT) using machine learning algorithms. We applied five different machine learning algorithms, namely Random Forest, Support Vector Machine (Linear Kernel), Support Vector Machine (Polynomial Kernel), K-Nearest Neighbors, and Naïve Bayes. These algorithms were tested using 10-fold cross validation and simulated various parameter tuning values. The results show that the Random Forest algorithm produces the best accuracy and kappa statistics values, so this algorithm is suitable for modeling predictive data of students graduating on time. This predictive model is expected to be useful for higher education management in designing their strategies to assist and improve student academic performance weaknesses in order to achieve graduation on time.

This Community Service is carried out by looking at the condition of the library's main books which are in disarray, the entry of books is not clear, lots of books are lost, whether they are borrowed, damaged, or for other reasons that are not clear, and many books are also destroyed without minutes so that an application is needed that can help the library to become more organized and monitored. The aim of PkM is to help optimize Digital-Based MAN 1 Bulukumba Library Services. PkM participants are librarians, teachers, and students of MAN 1 Bulukumba. The training implementation method consists of two stages, namely direct material presentation and mentoring, where material presentation is carried out in plenary and hands-on practice on how to install, introduce features and use them, and prospective library members also immediately try to open the application on their smartphone device. An analysis of the success of this PkM activity was carried out by observing the participants' ability to understand the material, the ability to use the application and the satisfaction of using the application, as well as the appearance of the application's features. The results of the activity were that this PkM succeeded in helping to optimize digital-based MAN 1 Bulukumba Library services. Participants are very able to understand the material and apply it in developing their library services such as being able to organize library books and Sistem Dewey Decimal Classification (DDC) are successfully implemented by classifying books according to their type and arranging the positions of these books so that they are easily found by library members. The ability to use applications by librarians is 100% because all library staff consisting of 4 librarians are able to provide library services through applications. Students and teachers who are prospective members of the library also managed to log in 100% to the MAN 1 Bulukumba Library application during the training. The satisfaction of the application users can be seen from the enthusiasm of the application users, and they have started to come and try to borrow books from the library. The development of display features and feature development is also very extraordinary. Librarians are able to adjust the appearance of features according to the identity of the school. There is a development of the barcode scan feature with a barcode that is made in each book and a notification feature via WhatsApp so that they can receive the latest information about borrowing their books. They can also transact using WhatsApp to extend the borrowing of books. Abstrak Pengabdian kepada Masyarakat (PkM) ini dilaksanakan dengan melihat kondisi buku induk perpustakaan yang amburadul, pencatatan buku masuk tidak jelas, banyak sekali buku-buku yang hilang, entah itu dipinjam, rusak, atau alasan lain yang tidak jelas, dan banyak juga buku dimusnahkan tanpa berita acara sehingga dibutuhkan suatu aplikasi yang dapat membantu perputakaan agar menjadi lebih terorganisir dan terpantau. Tujuan PkM yaitu untuk membantu Optimalisasi Layanan Perpustakaan MAN 1 Bulukumba Berbasis Digital. Peserta PkM yaitu pustakawan, guru, dan siswa-siswa MAN 1 Bulukumba. Metode pelaksanaan pelatihan terdiri atas dua tahapan yaitu pemaparan materi langsung dan pendampingan, dimana pemaparan materi dilakukan secara pleno dan paktek langsung bagaimana instalasi, pengenalan fitur-fitur dan penggunaannya, serta para calon anggota perpustakaan juga langsung mencoba membuka aplikasi di perangkat smartphone mereka. Analisis keberhasilan kegiatan PkM ini dilakukan dengan observasi kemampuan peserta memahami materi, kemampuan penggunaan aplikasi dan kepuasan penggunaan aplikasi, serta tampilan fitur aplikasi. Hasil kegiatan yaitu PkM ini berhasil membantu optimalisasi layanan Perpustakaan MAN 1 Bulukumba berbasis digital. Peserta sangat mampu memahami materi dan menerapkannya dalam mengembangkan pelayanan perpustakaannya seperti mampu mengorganisir buku-buku perpustakaan dan materi Sistem Dewey Decimal Classification (DDC) berhasil diterapkan dengan mengklasifikasikan buku sesuai dengan jenisnya dan mengatur posisi buku-buku tersebut agar mudah ditemukan oleh anggota perpustakaan. Kemampuan penggunaan aplikasi oleh pustakawan sudah 100% karena seluruh staf perpustakaan yang terdiri atas 4 orang pustakawan mampu memberikan pelayanan perpustakaan melalui aplikasi. Siswa dan guru yang menjadi calon anggota perpustakaan juga berhasil 100% login ke aplikasi Perpustakaan MAN 1 Bulukumba pada saat pelatihan. Untuk kepuasan pengguna aplikasi sendiri terlihat dari antusiasme pengguna aplikasi, dan sudah mulai berdatangan mencoba meminjam buku di perpustakaan. Perkembangan tampilan fitur dan pengembangan fitur juga sangat luar biasa. Pustakawan mampu menyesuaikan tampilan fitur sesuai dengan identitas sekolah. Ada pengembangan fitur scan barcode dengan barcode yang dibuat di setiap buku dan fitur notifikasi via whatsapp sehingga informasi terkini mengenai peminjaman buku mereka dapat mereka terima. Mereka juga dapat bertransaksi menggunakan whatsapp untuk perpanjangan peminjamam buku.

KNN categorization is simple and successful in healthcare. In this research's example case study, the KNN algorithm classified the new record as "Abnormal." The classification method began with choosing K, then calculating the Euclidean distance between the new record and the training set, finding the K nearest neighbors, then classifying the new record based on those K neighbors. The findings show that the KNN algorithm is effective in healthcare and highlight several shortcomings that should be addressed in future study. Weighting variables, choosing the best K value, and handling non-uniform data are these restrictions. The findings show the KNN algorithm's medical potential.

The objective of the study was to forecast the value of oil and gas exports in Indonesia using the ARIMA Box-Jenkins. With this prediction, it is hoped that it can be a study for future policy making. This oil and gas export data is obtained from the Indonesian Central Bureau of Statistics (BPS) website, in raw data from January 2010 to March 2022. This data is predicted using the ARIMA method with the help of R software. The stages of data analysis with ARIMA include: data stationary test, build the model indication, parameter estimation and significance test, and residual diagnostic test of the model. The results of data analysis conducted in this study show that there are 3 indications of models that were generated, namely ARIMA(1,1,0); ARIMA(0,1,1); and ARIMA(1,1,0). From these 3 model indications, the best model was ARIMA(0,1,1) with AIC value of 2047.65.

The national economics were horribly unsettled by covid-19 pandemic. Domestic consumption level fell sharply because the long post-pandemic recovery had severely impacted production and trade sectors where Small and Medium Enterprises do business most. Unhealthy business climate becomes pivotal moment for academicians to review the capability of Small and Medium Enterprises to survive the effect of covid-19 pandemic. The review was carried out by analyzing the contribution of managerial ability and entrepreneurial motivation to business performance through the mediation of business climate. East Java was selected as the scope of research. Number of sample was 120 Small and Medium Enterprises sorted with purposive sampling. Primary data were obtained through questionnaire. Analytical method was Partial Least Square operated with SmartPLS. Result of research showed that the significant impact of managerial ability and entrepreneurial motivation on business performance has made Small and Medium Enterprises consider as necessary to improve the potential and effectiveness of business management that has been applied. The situation of covid-19 pandemic also compelled Small and Medium Enterprises to strengthen entrepreneurial motivation to keep business performance increasing.

This study was the development of digital teaching materials in the era of the industrial revolution 4.0 era is a type of development research or R&D. The development of teaching materials in this study adapted the software development life cycle (SDLC) development model. Based on the results and discussion, we can conclude that the design and development of digital teaching material can be improve the effectiveness of the learning process and the use of online learning will be a new method/ approach of learning systems in the industrial revolution 4.0.

The objective of this study is to compare the different methods which are effective in predicting data of the short-term effect of COVID-19 confirmed cases and DJI closed stock market in the US. Data for confirmed cases of COVID-19 has been obtained from Worldometer, the database of Johns Hopkins University and the US stock market data (DJI) was obtained from Yahoo Finance. The data starts from 20 January 2020 (first confirmed COVID-19 case the US) to 06 December 2020 and DJI data covers 21 January 2019 to 04 December 2020. COVID-19 data was tested for the period 30 November to 06 December and DJI from 25 November 2020 to 04 December. From the result, we find that the method SutteARIMA was found more suitable to calculate the daily forecasts of COVID-29 confirmed cases and DJI in the US and this method has been used in this study. For the evaluation of the prediction methods, the accuracy measure means absolute percentage error (MAPE) has been used. The MAPE value with the SutteARIMA of 0.56 and 0.60 for COVID-19 and DJI stock respectively was found to be smaller than the MAPE value with ARIMA method.

This study is a quantitative research using bibliometric analysis. This study aimed to find out more detail about the “Statistics: A Journal of Theoretical and Applied Statistics” or SJTAS which was published during 1985-2021. This was seen from the topic of study, country productivity, author contributions, and analysis of their citation. The data in this study were taken from the Scopus database using keywords: (ISSN(0233-1888) OR ISSN(1029-4910)). The results obtained from the Scopus database are 1.798 documents. The average article citation fluctuates annually and the highest article citation is in 2018. Keywords from articles published in the SJTAS are dominated by topics: order statistics (55 articles), asymptotic normality (43 articles), bootstrap (33 articles), exponential distribution (32 articles), and consistency (31 articles).

The inflation rate, particularly in South Sulawesi Province from year to year, is found to be very unstable, so that an effort to overcome the instability of the inflation rate is highly needed. One of the efforts that can be used is to carry out a process of forecasting the inflation rate, so that the government can predict the inflation rate properly in order to realize the sustainable economic growth. The aim of this study was to forecast Inflation Cases in South Sulawesi Province. The forecasting carried out in this study used the Exponential Smoothing method. Exponential Smoothing is a method that will take into account average (smoothing) the data of the past exponentially by repeating calculations continuously using the latest data. In this study, 2 Exponential Smoothing methods were compared, namely: Single Exponential Smoothing (SES) and Double Exponential Smoothing (DES) which were used to obtain prediction results and evaluate the results of predictions using the Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) methods. The smallest MAPE value was obtained when using the Single Exponential Smoothing (SES) method when the value ɑ = 0.1 with the MSE value of 0.5567 and MAPE value of 265.7126 and the Double Exponential Smoothing (DES) method when the value ɑ = 0.3 and with the MSE value of 4,256 and MAPE value of 574,519. Thus, the Single Exponential Smoothing (SES) method was regarded as the best method in predicting the inflation rate in South Sulawesi Province.

The aim of this study is to determine the association between temperature and humidity in relation to COVID-19 above 3 degrees C. This was carried out in the cities of Bandung and Surabaya which have temperatures of about 22 degrees C to 31 degrees C. Data was analyzed using descriptive analysis and the Pearson and Spearman correlation for normally and abnormally distributed data. The results showed that there was no association between people under monitoring (ODP)/close contact, patients under surveillance (PDP)/suspect, and COVID-19 confirmed cases in relation to the temperature and humidity in Bandung and Surabaya. Furthermore, there was no relationship between temperature and humidity with ODP, PDP, and COVID-19 Confirmed cases in both cities, because they had a comfortably wet category (RH > 70%). This results are expected to provide information to the government that weather cases in Indonesia (temperatures around 26 degrees C-30 degrees C with humidity > 60%) do not affect the spread of COVID-19. In addition, it is expected that further studies would be carried out on other factors that influence the spread of COVID-19 in Indonesia, for example, how the level of alternating flow in and/ or out of the population into an area.

The aim of this study is to predict 200.000 cases of Covid-19 in Spain. Covid-19 Spanish confirmed data obtained from Worldometer from 01 March 2020 – 17 April 2020. The data from 01 March 2020 – 10 April 2020 using to fitting with data from 11 April – 17 April 2020. For the evaluation of the forecasting accuracy measures, we use the mean absolute percentage error (MAPE). Based on the results of SutteARIMA fitting data, the accuracy of SutteARIMA for the period 11 April 2020 - 17 April 2020 is 0.61% and we forecast 20.000 confirmed cases of Spain by the WHO situation report day 90/91 which is 19 April 2020 / 20 April 2020.

This activity was carried out with the aim of: (1) Increasing teacher knowledge in processing and analyzing research data; (2) Developing teacher awareness and knowledge about the importance of data management in research data analysis; (3) Improving the insight, ability and skills of teachers in utilizing data to make it more informative by analyzing data using excel software; and (4) Reducing the number of teachers who perform data processing and analysis intuitively and manually in the computing era. The results of the implementation of this activity were: (1) The knowledge of teachers in processing and analyzing research data was increased; (2) The awareness and knowledge of teachers about the importance of processing and analyzing research data were developed; (3) The insight, ability and skills of teachers in utilizing data to be more informative with proper data processing and analysis were improved; and (4) The number of teachers who perform data processing and analysis intuitively and manually in the computing era was reduced. Abstrak Pengolahan data menggunakan Anaysis Toolspack dilakukan dalam bentuk pelatihan bagi guru-guru di Kab. Barru bekerjasama dengan UPT SMA Negeri 1 Barru Kabupaten Takalar. Pelatihan bertempat di SMA Negeri 1 Barru Kabupaten Barru dan dilaksanakan secara daring dengan menggunakan Zoom. Tujuan dari pelatihan ini adalah agar guru terampil dalam menggunakan paket statistik yang dimiliki Excel untuk mengolah data dan mengolah data menjadi satu informasi. Hasil pelatihan menunjukkan bahwa rata-rata kemampuan guru dalam menggunakan statistika pada paket excel analysis tools pack dalam mengolah dan mengolah data setelah pelatihan lebih baik (meningkatkan) daripada sebelum pelatihan.

This study focuses on the novel forecasting method (SutteARIMA) and its application in predicting Infant Mortality Rate data in Indonesia. It undertakes a comparison of the most popular and widely used four forecasting methods: ARIMA, Neural Networks Time Series (NNAR), Holt-Winters, and SutteARIMA. The data used were obtained from the website of the World Bank. The data consisted of the annual infant mortality rate (per 1000 live births) from 1991 to 2019. To determine a suitable and best method for predicting Infant Mortality rate, the forecasting results of these four methods were compared based on the mean absolute percentage error (MAPE) and mean squared error (MSE). The results of the study showed that the accuracy level of SutteARIMA method (MAPE: 0.83% and MSE: 0.046) in predicting Infant Mortality rate in Indonesia was smaller than the other three forecasting methods, specifically the ARIMA (0.2.2) with a MAPE of 1.21% and a MSE of 0.146; the NNAR with a MAPE of 7.95% and a MSE of 3.90; and the Holt-Winters with a MAPE of 1.03% and a MSE: of 0.083.

PurposeThis paper aims to reveal the effect of organizational learning on market orientation, job satisfaction on market orientation, organizational learning on business innovation, job satisfaction on business innovation and market orientation on business innovation.Design/methodology/approachResearch was designed to use quantitative approach to understand causal relationship of variables. partial least squares structural equation modeling (PLS-SEM) was used to facilitate this approach. Questionnaire was given to 46 dairy cattle milk cooperatives in East Java, Indonesia.FindingsResearch findings are explained as follows: both high organizational learning and high job satisfaction can produce high market orientation, organizational learning reduces business innovation, job satisfaction increases business innovation and market orientation reduces business innovation of dairy cattle milk cooperatives in East Java, but this reduction is not statistically significant.Research limitations/implicationsThis research has identified that business innovation is affected by job satisfaction, while market orientation is affected by organizational learning and job satisfaction. Next research shall be conducted on another business type or business group but in greater population.Practical implicationsIt is expected that the results of this research will provide guidance for dairy cattle milk cooperatives in East Java concerning with how to improve market orientation and business innovation based on organizational learning and job satisfaction.Originality/valueThis research has determined factors that affect market orientation and examined its impact on business innovation after observing the aspects of organizational learning and job satisfaction.

Calculation errors in forecasting a data are very important from a forecasting process. The high level of forecasting accuracy will affect the level of confidence in forecasting decision making.

The objective of this study was to determine whether Covid-19 cases in the world would have reached 4 million cases with the SutteARIMA method forecasting approach. Data from this study were obtained from the Worldometer from 1 March 2020 to 05 May 2020. Data were used for data fitting from 1 March 2020 to 28 April 2020 (29 April 2020 – 05 May 2020). The data fitting is used to see the extent of the accuracy of the SutteARIMA method when predicting data. The MAPE method is used to see the level of data accuracy. Results of forecasting data for the period from 29 April 2020 to 05 May 2020: 72,731; 84,666; 92,297; 100,797; 84,312; 81,517; 74845. The accuracy of SutteARIMA for the period 30 April 2020 – 06 May 2020 shall be 0.069%. Forecast results for as many as 4 million cases, namely from 08 May 2020 to 10 May 2020: 3,966,786; 4,047,328 and 4,127,747. The SutteARIMA method predicts that 4 million cases of Covid-19 in the world will be reported on the WHO situation report on the day 110/111 or 09 May 2020/10 May 2020.

Masalah surveilans atau pemantuan kesehatan ibu dan anak (KIA) masih ditandai dengan belum terlapor dan tercatat dengan sempurna, sepenuhnya dan tepat waktu semua peristiwa kehamilan dan persalinan di wilayah kerja bidan kelurahan. Sasaran surveilans ditujukan kepada seluruh peristiwa kelahiran bayi dari seluruh kehamilan yang tercatat. Sehingga metode dan/atau strategi yang dilakukan untuk mencapai kondisi yang diharapkan yaitu Surveilans dan Community development. Hasil: (1) meningkatnya partisipasi masyarakat dalam melaporkan diri ketika hamil dan updating data kependudukan; (2) meningkatnya pengetahuan dan keterampilan masyarakat mengenai kelahiran bayi, ibu hamil, dan kependudukan.