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All Journal IQTISHODUNA Jurnal Ekonomi Modernisasi The Asian Journal of Technology Management (AJTM) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Studi Komunikasi Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Jurnal Varian Abdi Dosen : Jurnal Pengabdian Pada Masyarakat Journal of Applied Science, Engineering, Technology, and Education Variansi : Journal of Statistics and Its Application on Teaching and Research Mattawang: Jurnal Pengabdian Masyarakat JINAV: Journal of Information and Visualization Quantitative Economics and Management Studies LOSARI: Jurnal Pengabdian Kepada Masyarakat Jurnal Riset dan Inovasi Pembelajaran Panrannuangku Jurnal Pengabdian Masyarakat EduLine: Journal of Education and Learning Innovation Daengku: Journal of Humanities and Social Sciences Innovation ARRUS Journal of Social Sciences and Humanities ARRUS Journal of Mathematics and Applied Science al-fikrah: Jurnal Manajemen Pendidikan Seminar Nasional Pengabdian Kepada Masyarakat VARIANSI: Journal of Statistics and Its Application on Teaching and Research Seminar Nasional Hasil Penelitian LP2M UNM ARRUS Jurnal Pengabdian Kepada Masyarakat
Ahmar, Ansari Saleh
Department Of Statistics, Universitas Negeri Makassar, 90223, Makassar, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Pemodelan Pertumbuhan Ekonomi Provinsi Sulawesi Selatan dengan Menggunakan Regresi Data Panel Misriani Suardin; Muhammad Nadjib Bustan; Ansari Saleh Ahmar
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 2, No 3 (2020)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm14637

Abstract

Abstract. Economic growth is a process for change the economic condition a country or regional by continuously for the better condition as long as definite period. Economic growth in South Sulawesi for 2013-2016 have up and down because many factors have influence it. Like jobless, human capital index, regional revenue, expenditure, and total population. This research was conducted to determine the factors that influence economic growth in South Sulawesi by using data panel regression methods. Panel data regression is a regression by using panel data. Panel data is a statistics analysis method that combines between time series data and cross section data. The result indicates that the result if the regression analysis on the =5% show that the best panel data regression model is random effect model and human capital index variable have significant effect on economic growth with probability value about 0,0227. Meanwhile, jobless, regional revenue, expenditure, and total population no significant.Keywords: Panel Data Regression, Economic Growth, Common Effect Model, Fixed Effcet Model, Random Effect Model
Pengolahan data menggunakan Toolspack Analysis Excel pada guru-guru di Kabupaten Takalar Rusli Rusli; Abdul Rahman; Ansari Saleh Ahmar; Sahid Sahid; Hastuty Hastuty
Seminar Nasional Pengabdian Kepada Masyarakat Vol 2019, No 3 (2019): PROSIDING 3
Publisher : Seminar Nasional Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (128.768 KB)

Abstract

Data processing using the Anaysis Toolspack is carried out in the form of training for junior high school teachers in Takalar district, in collaboration with the education and culture department of youth and sports in Takalar district. The training was attended by 34 teachers who were held in the office of the education and culture culture of the youth and sports district of Takalar. The purpose of this training is for skilled teachers to use statistical packages owned by Excel to process data and process data into one information. The results of the training show that the average ability of teachers to use statistics in the excel analysis toolspack package in processing and processing data after training is better than before training
Bibliometric Analysis of “Statistics: A Journal of Theoretical and Applied Statistics” on 1985-2021 Period Ansari Saleh Ahmar; Miguel Botto-Tobar; Abdul Rahman; Angela Diaz Cadena; R. Rusli; Rahmat Hidayat
Journal of Applied Science, Engineering, Technology, and Education Vol. 4 No. 1 (2022)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (552.088 KB) | DOI: 10.35877/454RI.asci1135

Abstract

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).
Optimization of Digital-Based Library Services in MAN 1 Bulukumba: Optimalisasi Layanan Perpustakaan Berbasis Digital di MAN 1 Bulukumba Sutamrin Sutamrin; Abdul Rahman; Rusli Rusli; Ansari Saleh Ahmar; Khadijah Khadijah
Mattawang: Jurnal Pengabdian Masyarakat Vol. 3 No. 4 (2022)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (898.589 KB) | DOI: 10.35877/454RI.mattawang1336

Abstract

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.
Forecast Error Calculation with Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) Ansari Saleh Ahmar
JINAV: Journal of Information and Visualization Vol. 1 No. 2 (2020)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav303

Abstract

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.
Forecasting the Value of Oil and Gas Exports in Indonesia using ARIMA Box-Jenkins Ansari Saleh Ahmar; Miguel Botto-Tobar; Abdul Rahman; Rahmat Hidayat
JINAV: Journal of Information and Visualization Vol. 3 No. 1 (2022)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav260

Abstract

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.
Cross-Validation and Validation Set Methods for Choosing K in KNN Algorithm for Healthcare Case Study Robbi Rahim; Ansari Saleh Ahmar; Rahmat Hidayat
JINAV: Journal of Information and Visualization Vol. 3 No. 1 (2022)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav1557

Abstract

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.
Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-Winters Suwardi Annas; Ansari Saleh Ahmar; Rahmat Hidayat
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.%v.%i.1003

Abstract

Unhealthy and unsafe sanitation will make it easier for various diseases to attack the body. In addition, unsafe sanitation will also affect a country's economy, including declining welfare, tourism losses, and environmental losses due to the loss of productive land. The research aimed to estimate the welfare cost of premature deaths based on unsafe sanitation risks using the SutteARIMA, Neural Network Time Series, and Holt-Winters. The study analyzed estimates and projections of the welfare cost of premature deaths based on the risks of unsafe sanitation of BRICS countries (Brazil, Russia, Indonesia, China, and South Africa). The data in this research used secondary data. Secondary time series data was taken from the Environment Database of the OECD. Stat. (Mortality and welfare cost from exposure to environmental risks). The data on the study was based on variables: welfare cost of premature deaths, % GDP equivalent, risk: unsafe sanitation, age: all, sex: both, unit: percentage, and data from 2005 to 2019. The three forecasting methods (SutteARIMA, Neural Network Time Series, and Holt-Winters) were juxtaposed in fitting data to see the forecasting methods' reliability and accuracy. The accuracy of forecasting results was compared based on MAPE and MSE values. The results of the research showed that the SutteARIMA and NNAR(1,1) methods were best used to predict the welfare cost of premature deaths in view of unsafe sanitation risks for BRICS countries.
Machine Learning Algorithms with Parameter Tuning to Predict Students’ Graduation-on-time: A Case Study in Higher Education Rizal Bakri; Niken Probondani Astuti; Ansari Saleh Ahmar
Journal of Applied Science, Engineering, Technology, and Education Vol. 4 No. 2 (2022)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci1581

Abstract

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.
Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-Winters Suwardi Annas; Ansari Saleh Ahmar; Rahmat Hidayat
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1685

Abstract

Unhealthy and unsafe sanitation will make it easier for various diseases to attack the body. In addition, unsafe sanitation will also affect a country's economy, including declining welfare, tourism losses, and environmental losses due to the loss of productive land. The research aimed to estimate the welfare cost of premature deaths based on unsafe sanitation risks using the SutteARIMA, Neural Network Time Series, and Holt-Winters. The study analyzed estimates and projections of the welfare cost of premature deaths based on the risks of unsafe sanitation of BRICS countries (Brazil, Russia, Indonesia, China, and South Africa). The data in this research used secondary data. Secondary time series data was taken from the Environment Database of the OECD. Stat. (Mortality and welfare cost from exposure to environmental risks). The data on the study was based on variables: welfare cost of premature deaths, % GDP equivalent, risk: unsafe sanitation, age: all, sex: both, unit: percentage, and data from 2005 to 2019. The three forecasting methods (SutteARIMA, Neural Network Time Series, and Holt-Winters) were juxtaposed in fitting data to see the forecasting methods' reliability and accuracy. The accuracy of forecasting results was compared based on MAPE and MSE values. The results of the research showed that the SutteARIMA and NNAR(1,1) methods were best used to predict the welfare cost of premature deaths in view of unsafe sanitation risks for BRICS countries.
Co-Authors Abdul Rahman Abdul Rahman Abdussakir Abdussakir Absussakir Abdussakir Achmad Sani Supriyanto Agus Nasir Ahmad Rifad Riadhi Ahmad Talib Akbar Iskandar Akbar Iskandar Alfairus, Muh. Qodri Ali Mokhtar Alief Imron Juliodinata Alok Kumar Panday Alsa, Yudhistira Ananda Andika Isma ANDIKA SAPUTRA Angela Diaz Cadena Asfar Asfar Asmar Asmar, Asmar Astuti, Niken Probondani Aswi, Aswi Ayu Rahayu Azzajjad, Muhammad Fath Boj del Val, Eva Boj, Eva Bustan, M Nadjib Dary Mochamad Rifqie Della Fadhilatunisa Dewi Fatmarani Surianto Dewi Satria Ahmar Djawad, Yasser Abd. Ersa Karwingsi Eva Boj Faizal Arya Samman Fathahillah Fathahillah Hamzah Upu Hardianti Hafid Hastuty Hastuty Hastuty Hastuty Hastuty Musa Herman Herman Hidayat M., Wahyu Ifriana Ifriana Ilimu, Edi Irwan Irwan Irwan Irwan Isma Muthahharah Jamaluddin Jamaluddin Kamaluddin Kamaluddin Kasmudin Mustapa Khadijah Khaeruddin Khaeruddin Lince, Ranak M. Miftach Fakhri Maemunah Magfirah Manalu, Yessi Febianti Mansyur Mansyur Marni Marni, Marni Meliyana R, Sitti Masyitah Miguel Botto-Tobar Misriani Suardin Mohd. Rizal Mohd. Isa Muhammad Abdy Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Farhan Muhammad Kasim Aidid Muhammad Kasim Aidid Muhammad Nadjib Bustan Muhammad Nadjib Bustan Muhammad Nusrang Muliadi Muliadi N. Nurahdawati Nachnoer Arss Nasrul Ihsan Niken Probondani Astuti Niken Probondani Astuti Novi Afryanthi S. Nur Anisa Nurdin Arsyad, Nurdin Nurhikmawati, Nurhikmawati Nurul Khofifah Salsabila Parkhimenko Vladimir Anatolievich Patmasari, Andi Poerwanto, Bobby R. Ruliana R. Rusli R. Rusli R. Rusli Rahman, Abdul Rahman, Muhammad Fatur Rahmat Hidayat Rahmat Hidayat Rais, Zulkifli Rajesh Kumar Ramli Umar Riny Jefri Rizal Bakri Robbi Rahim Rosidah Rosidah Rosidah Rosidah Ruliana Ruliana Ruliana, Ruliana Rusli Rusli Rusli Rusli Rusli Rusli Rusli Rusli Rustam, Sitti Nailah Sahid Sahid Salim Al Idrus Salim Al Idrus Sapto Haryoko Sarinah Emilia Tonio Shofiyah Al Idrus Singh, Pawan Kumar Siti Nurazizah Auliah Sitti Masyitah Meliyana R. Sitti Rahmawati Sobirov, Bobur Sri Hastuti Virgianti Pulukadang Sri Muliani Sriwahyuni, Andi Ayu Suci Lestari Sutamrin, Sutamrin Suwardi Annas Suwardi Annas Suwardi Annas Syafruddin Side Tabash, Mosab Tri Santoso Triutomo, Agung wahyuni wahyuni Yunus, Asmar Zakiyah Mar'ah Zakiyah Mar'ah Zamil Wahab Zulkifli Rais