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Geographically Weighted Regression (GWR) Modeling in Identifying Factors Affecting the Gender Empowerment Index in Indonesia Meliyana, Sitti Masyitah; Ahmar, Ansari Saleh; Rahman, Abdul
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 5 No. 4 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4449

Abstract

This study aims to analyze the factors influencing the Gender Empowerment Index (GEI) in Indonesia using the Geographically Weighted Regression (GWR) method. The variables used in this study include the proportion of women in managerial positions, women’s income contribution, the proportion of professional workers, reported health complaints, and the proportion of women in parliament. The findings indicate that, among the five independent variables examined, only two variables significantly affect the dependent variable: the proportion of women in managerial positions (X1) and the percentage of women reporting health complaints (X5). This is evidenced by their respective probability values (Pr(>F)) of 0.0045 and 0.0128, which are below the 0.05 significance threshold. This implies that X1 and X5 have a statistically significant influence in the model. The GWR model was found to be the most suitable compared to other models, with an AIC value of 186.72 and an R² of 92.03%, indicating superior model performance in capturing spatial and non-spatial effects across regions.
Workshop on Student Graduation Decisions Using Statistical Methods at Takalar State Senior High School 7 Annas, Suwardi; Ahmar, Ansari Saleh; Rais, Zulkifli; H.S, Rahmat; Tri Utomo, Agung
ARRUS Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 2 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.abdiku4458

Abstract

This community service program was conducted at SMA Negeri 7 Takalar to enhance teachers’ ability to utilize statistical methods specifically logistic regression to support data-driven graduation decisions. The training addressed challenges related to manual graduation assessment processes that often lack objective analytical support. Participants were introduced to the basic concepts of logistic regression, followed by hands-on practice using an interactive R Shiny dashboard to analyze student data and estimate graduation probabilities. The results indicate that teachers were able to understand and apply statistical analysis procedures, interpret logistic regression outputs, and recognize the importance of evidence-based decision-making. This activity not only improved teachers’ data literacy but also supported digital transformation efforts in education and strengthened collaboration between Universitas Negeri Makassar and SMA Negeri 7 Takalar. The program is expected to contribute to more accurate, transparent, and data-informed graduation assessments in the future.
Application of Neural Network Time Series (NNAR) and ARIMA to Forecast Infection Fatality Rate (IFR) of COVID-19 in Brazil Ahmar, Ansari Saleh; Boj, Eva
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.372

Abstract

Forecasting is a method that is often used to view future events using past time data. Past time data have useful information to use in obtaining the future. The aim of this study was to forecast infection fatality rate (IFR) of COVID-19 in Brazil using NNAR and ARIMA. ARIMA and NNAR are used because (1) ARIMA is a simple stochastic time series method that can be used to train and predict future time points and ARIMA also capable of capturing dynamic interactions when it uses error terms and observations of lagged terms; (2) the Artificial Neural Network (ANN) is a technique capable of analyzing certain non-linear interactions between input regressor and responses, and Neural Network Time Series (NNAR) is one method of ANN in which lagged time series values were used as inputs to a neural network. Data included in this study were derived from the total data of confirmed cases and the total data of death of COVID-19. The data of COVID-19 in Brazil from February 15, 2020 to April 30, 2020 were collected from the Worldometer (https://www.worldometers.info/coronavirus/) and Microsoft Excel 2013 was used to build a time-series table. Forecasting was accomplished by means of a time series package (forecast package) in R Software.  Neural Network Time Series and ARIMA models were applied to a dataset consisting of 76 days. The accuracy of forecasting was examined by means of an MSE. The forecast of IFR of COVID-19 in Brazil from May 01, 2020 to May 10, 2020 with NNAR (1,1) model was around in 6,85% and ARIMA (0,2,1) was around in 7.11%.
Optimalisasi Peran Mahasiswa KKN dalam Mendukung Pembangunan Desa Berbasis Potensi Lokal Hastuty, Hastuty; Rusli, Rusli; Ahmar, Ansari Saleh; Rahman, Abdul; Saputra, Andika
Panrannuangku Jurnal Pengabdian Masyarakat Vol. 5 No. 4 (2025)
Publisher : Lembaga Penelitian dan Pengembangan Teknologi dan Rekayasa, Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/panrannuangku4358

Abstract

Kuliah Kerja Nyata (KKN) merupakan bentuk nyata pengabdian mahasiswa yang berfungsi menjembatani ilmu pengetahuan perguruan tinggi dengan realitas kehidupan masyarakat, khususnya di desa, serta menjadi strategi penting dalam mendukung pembangunan desa berkelanjutan. Artikel ini membahas upaya optimalisasi peran mahasiswa KKN di Kelurahan Lemoe, Kecamatan Bacukiki, Kota Parepare, dengan fokus pada pemanfaatan potensi lokal. Pelaksanaan KKN dimulai dengan tahap observasi, dilanjutkan dengan presentasi di hadapan Dosen Pembimbing Lapangan (DPL), aparat kelurahan, dan tokoh masyarakat. Program kerja mahasiswa difokuskan pada tiga aspek utama. Pertama, digitalisasi desa melalui pengembangan Website Kelurahan Lemoe. Kedua, pengembangan produk lokal, berupa inovasi olahan daun kelor menjadi Snack Bar Bergizi serta pemanfaatan jambu mete, menjadi Selai Jambu Mete. Ketiga, program kemasyarakatan, mencakup sosialisasi “Lingkungan Sekolah Sehat Bebas Perundungan”, seminar hukum bertema “Kenali dan Identifikasi Tanahmu”, serta berbagai kegiatan sosial seperti senam bersama dan partisipasi dalam perayaan 17 Agustus. Hasil dari pelaksanaan KKN ini memberikan kontribusi nyata berupa peningkatan kapasitas aparatur kelurahan dan masyarakat, serta melahirkan produk bernilai ekonomi berbasis potensi lokal. Dengan adanya dukungan penuh dari aparat kelurahan serta partisipasi aktif masyarakat, KKN berfungsi sebagai sarana pengabdian yang adaptif, inovatif, dan berkelanjutan, sekaligus memperkuat daya saing desa berbasis sumber daya yang dimilikinya.
Statistical Dashboards and Business Intelligence in Campus Information Systems: A Bibliometric Review of Implementation Trends Ansari Saleh Ahmar; Agung Triutomo
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 3 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci2969

Abstract

Campus academic information systems have become mission-critical infrastructure in higher education, yet a significant paradox persists. Many universities operate monolithic architectures that consolidate student data and administrative functions within unified platforms—offering inherent security advantages including centralized authentication, unified access control, and simplified vulnerability monitoring. However, scholarly discourse examining how these secure integrated systems can simultaneously achieve advanced business intelligence capabilities remains remarkably thin. This bibliometric study analyzes 749 publications from Scopus (2010-2025) to map the intellectual landscape of campus information systems research, with particular attention to security frameworks and statistical dashboard implementations. The methodology combines linear regression trend analysis (? = 2.54, p = 0.00135, R² = 0.5317), Bradford's Law, Lotka's Law, and k-means clustering (k = 9). Results reveal statistically significant publication growth (CAGR = 1.46%), accumulating 6,039 citations (mean = 8.06) across 1,945 authors from 86 countries. Indonesia dominates contributions (26.1%), followed by China (10.3%) and the United States (8.1%). Thematic analysis identifies nine research clusters, with security-focused studies employing PTES and OWASP methodologies achieving 83% intrusion detection accuracy, while governance evaluations using COBIT and ISO 27001 reveal system maturity gaps. Critically, fewer than 10% of publications address real-time analytics or decision support visualization within secure monolithic architectures. The collaboration index (3.03 authors/document) and degree of collaboration (83.2%) indicate robust interdisciplinary practices. Findings suggest that while security research has matured, significant gaps persist in integrating business intelligence dashboards with secure monolithic systems—highlighting urgent need for research bridging data protection frameworks with analytical capabilities.
Co-Authors - Asmar Abdul Rahman Abdul Rahman Abdussakir Abdussakir Absussakir Abdussakir Achmad Sani Supriyanto Agung Triutomo Agus Nasir Ahmad Rifad Riadhi Ahmad Talib Aidid, Muhammad Kasim Akbar Iskandar Alfairus, Muh. Qodri Ali Mokhtar Alief Imron Juliodinata Alok Kumar Panday Alsa, Yudhistira Ananda Andika Isma ANDIKA SAPUTRA Anggreni, Afrillia Asfar Asmar Asmar, Asmar Astuti, Niken Probondani Aswi, Aswi Ayu Rahayu Azzajjad, Muhammad Fath Boj del Val, Eva Boj, Eva Botto-Tobar, Miguel Bustan, M Nadjib Cadena, Angela Diaz Dary Mochamad Rifqie Della Fadhilatunisa Dewi Fatmarani Surianto Dewi Satria Ahmar Djawad, Yasser Abd. Ersa Karwingsi Eva Boj Faizal Arya Samman Fathahillah Fathahillah H.S, Rahmat Halim, Patmawati 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 Kusmaladewi, K. Lince, Ranak M. Miftach Fakhri 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 Abdy Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Farhan Muhammad Kasim Aidid Muhammad Kasim Aidid Muhammad Nadjib Bustan Muhammad Nadjib Bustan Muhammad Nusrang Muliadi N. Nurahdawati Nachnoer Arss Nasrul Ihsan Niken Probondani Astuti Novi Afryanthi S. Nur Anisa Nurdin Arsyad, Nurdin Nurhikmawati, Nurhikmawati Parkhimenko Vladimir Anatolievich Patmasari, Andi Poerwanto, Bobby Purnama Ningsih R. Ruliana R. Rusli R. Rusli Raden Mohamad Herdian Bhakti Rahman, Abdul Rahman, Muhammad Fatur Rahmat Hidayat 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, R. Rustam, Sitti Nailah Sahid Salim Al Idrus Salim Al Idrus Salsabila, Nurul Khofifah Sapto Haryoko Shofiyah Al Idrus Singh, Pawan Kumar Siswahyudianto Siti Nurazizah Auliah Sitti Masyitah Meliyana R. Sitti Rahmawati Sobirov, Bobur Sri Hastuti Virgianti Pulukadang Sri Muliani, Sri Sriwahyuni, Andi Ayu Suci Lestari Sutamrin, Sutamrin Suwardi Annas Suwardi Annas Syafruddin Side Tabash, Mosab Tonio, Sarinah Emilia Tri Santoso Triutomo, Agung Utomo, Agung Tri Wahab, Zamil wahyuni wahyuni Yunus, Asmar Zakiyah Mar'ah Zakiyah Mar'ah Zulkifli Rais