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All Journal BAKI (Berkala Akuntansi dan Keuangan Indonesia) JIKAP PGSD: Jurnal Ilmiah Ilmu Kependidikan M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Bisman (Bisnis dan Manajemen): The Journal of Business and Management Inferensi Didaktik : Jurnal Ilmiah PGSD STKIP Subang Abdimas Langkanae Indonesian Journal of Social and Educational Studies JTechLP Information Technology Education Journal Journal of Educational Technology, Curriculum, Learning, and Communication ARRUS Jurnal Pengabdian Kepada Masyarakat PENSOS: Jurnal Penelitian dan Pengabdian Pendidikan Sosiologi Journal of Innovative and Creativity Journal of Mathematics, Computation and Statistics (JMATHCOS) Jurnal Ekonomi, Manajemen, Akuntansi dan Keuangan Journal of Community Services and Development Celebes Science Education Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam
Rahmat Hidayat
Universitas Negeri Makassar
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Pelatihan Visualisasi Statistik Interaktif Menggunakan GeoGebra untuk Meningkatkan Pemahaman Konsep Statistika Siswa SMAN 4 Gowa Ansari Saleh Ahmar; Rahmat Hidayat; Muh. Imam Shadiq; Rika Saniarti; Indy Pratiwi HR; Fadhil Rochbini
Abdimas Langkanae Vol. 6 No. 2 (2026)
Publisher : Pustaka Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53769/jpm.v6i2.873

Abstract

Siswa SMAN 4 Gowa mengalami kesulitan menafsirkan ukuran pemusatan, simpangan baku, dan distribusi normal secara kontekstual. Kegiatan ini bertujuan meningkatkan pemahaman konseptual statistika siswa melalui pelatihan visualisasi interaktif menggunakan GeoGebra, dengan guru matematika sebagai mitra. Program meliputi sosialisasi, pelatihan konseptual dan praktik, proyek mini berbasis data, pendampingan guru, dan penyerahan modul. Evaluasi menggunakan desain satu kelompok tes awal–tes akhir terhadap 49 siswa dengan tes pemahaman konsep, observasi berbasis rubrik, dan kuesioner; data tes dianalisis dengan uji-t berpasangan. Rerata skor naik dari 70,51 menjadi 79,67 (selisih 9,16 poin; t(48) = 9,534; p < 0,001), dan 47 dari 49 siswa  mampu membuat histogram serta menjalankan simulasi distribusi normal secara mandiri sesudah pelatihan. Hasil ini menunjukkan perubahan skor jangka pendek, bukan bukti kausal keunggulan GeoGebra atas pembelajaran konvensional. Modul yang diserahkan merupakan bekal keberlanjutan yang penggunaannya masih perlu dipantau.
FINANCIAL LITERACY, CASHLESS PAYMENT USAGE, AND FINANCIAL PERFORMANCE OF MICRO AND SMALL ENTERPRISES IN INDONESIA Muh. Irshan Sachrir Sachrir; Andi Nurul Tenriwali Hasanuddin; Nurul Haeriyah Ridwan; Rahmat Hidayat
Berkala Akuntansi dan Keuangan Indonesia Vol. 11 No. 2 (2026): Berkala Akuntansi dan Keuangan Indonesia
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/baki.v11i2.87088

Abstract

This study examines how financial literacy and cashless payment usage influence the financial performance of micro and small enterprises (MSEs) in Indonesia. Drawing on the Resource-Based View (RBV) and the Technology Acceptance Model (TAM), financial literacy is positioned as an internal managerial capability, while cashless payment usage is viewed as technology adoption that supports transaction efficiency, transparency, and financial monitoring. A quantitative explanatory design was applied using cross-sectional survey data from 120 MSE owners who were directly involved in business financial management. The data were analyzed using PLS-SEM with SmartPLS. The findings show that financial literacy has a positive and significant effect on financial performance. MSE owners with better financial knowledge are more capable of preparing records, managing cash flow, separating business and personal finances, and calculating profit. Cashless payment usage also has a positive and significant effect, indicating that QR-based payments, electronic wallets, and mobile banking can strengthen transaction recording and business monitoring. The study contributes by integrating RBV and TAM in a single empirical framework and by showing that financial literacy and cashless payment usage work as complementary factors in improving MSE financial performance.
Comparison Of Bayesian Spatial Car Models For Estimating The Risk Of Diarrhea Cases In Makassar City Nurul Aulya Bakri; Wanda Yudi; Aswi Aswi; Rahmat Hidayat
SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Vol. 14 No. 2 (2025): Volume 14 Nomor 2 (September 2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/g2pj1d41

Abstract

Diarrhea continues to pose a significant public health challenge in Makassar City, with incidence varying across sub-districts. Mapping diarrhea risk is essential for public health planning, as it helps identify high-risk areas and allocate resources efficiently. Accurate spatial risk assessment supports targeted interventions and informs evidence-based health policies. This study aimed to identify areas with high and low relative risks (RR) of diarrhea cases using Bayesian spatial Conditional Autoregressive (CAR) models, specifically the Besag–York–Mollié (BYM) and Leroux approaches. The analysis was based on case data from 15 sub-districts in Makassar City in 2023. Model performance was assessed using the Deviance Information Criterion (DIC) and the Watanabe–Akaike Information Criterion (WAIC). The CAR-Leroux model with an Inverse Gamma (IG) hyperprior (0.5; 0.0005) was identified as the best-fitting model, providing the most reliable estimation of relative risk. Kepulauan Sangkarrang exhibited the highest RR, indicating a markedly elevated risk of diarrhea relative to the city average, while Biringkanaya District showed the lowest RR, reflecting a substantially lower risk compared to the average.
Implementation of DBSCAN for Earthquake Clustering in Indonesia with Potential Surface Damage Hardianti Hafid; Rahmat Hidayat; Rahmat H. S.
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7318

Abstract

Indonesia is one of the countries with the highest seismic activity in the world due to its location at the convergence of three major tectonic plates. Understanding earthquake distribution patterns is crucial for disaster mitigation efforts and policy planning. This study applies the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to cluster earthquake data in Indonesia based on magnitude and depth. The data used is secondary data from the Meteorology, Climatology, and Geophysics Agency (BMKG) for the period of January–December 2023. The research stages include data collection and preprocessing, applying the DBSCAN algorithm with the selection of Eps and MinPts parameters, and evaluating the clustering results using the silhouette coefficient and Davies-Bouldin Index (DBI). The results show that the combination of Eps = 0.5 and MinPts = 5 produces clusters with a silhouette coefficient of 0.3959 and a DBI of 0.7384, indicating a fairly good cluster structure. Visualization results reveal high-density clusters in active seismic zones and several smaller clusters representing specific earthquake characteristics. This study provides insights into the earthquake distribution patterns in Indonesia and demonstrates that DBSCAN effectively identifies complex cluster structures. The findings can serve as a reference for seismological studies and support earthquake disaster mitigation efforts.
Spatial Dynamics of Digital Society Index in Indonesia: A Spatial Autoregressive Approach Zakiyah Mar&#039;ah; Rahmat H. S.; Rahmat Hidayat
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.9217

Abstract

The equitable distribution of digital transformation in Indonesia is a strategic issue, given the importance of technology in supporting national development. Indeks Masyarakat Digital Indonesia (IDSI) or Indonesian Digital Society Index (IDSI) was developed to measure the level of digital literacy, inclusion, and digital infrastructure readiness at the provincial level. However, the distribution of IDSI values shows striking spatial disparities. This research aims to identify spatial dependency patterns and significant factors influencing IDSI using a Spatial Autoregressive (SAR) model. The data used is the 2024 IDSI from 34 provinces in Indonesia, with five independent variables: access and adoption of digital technology, learning ecosystem, ICT introduction, empowerment, and employment. A spatial autocorrelation test using Moran's I revealed a significant positive spatial dependency, indicating a clustered pattern in IDSI distribution. The Lagrange Multiplier test showed spatial dependency in the lag or response variable, making the SAR model suitable. Estimation results demonstrate that all five independent variables significantly impact IDSI, with a coefficient of determination (R²) of 0.98. These findings indicate that geographically proximate regions tend to have similar IDSI values. Therefore, spatial approaches like SAR are crucial for formulating national digital equity policies.
Hybrid Spatio-Temporal Modeling of Dengue Incidence Using ST-CAR-ARIMA with Remote Sensing Covariates in Makassar, Indonesia BQ Nurkhalishah K.; Aswi Aswi; Suwardi Annas; Rahmat Hidayat; Nur Salsabila Wero; Sukarna Sukarna
Journal of Mathematics, Computations and Statistics Vol. 9 No. 3 (2026): Volume 09 Issue 03 (September 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/yyrha036

Abstract

Dengue hemorrhagic fever (DHF) exhibits complex spatial and temporal dynamics that require analytical approaches capable of jointly accounting for geographic heterogeneity, temporal dependence, and environmental conditions. This study developed a hybrid spatio-temporal framework integrating a Bayesian Spatio-Temporal Conditional Autoregressive (ST-CAR) model with a Seasonal Autoregressive Integrated Moving Average (SARIMA) model to characterize and predict DHF incidence in Makassar City, Indonesia. Monthly DHF cases from 149 urban villages were analyzed over 32 months, from January 2022 to August 2024, together with remotely sensed environmental covariates represented by the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). A Bayesian ST-CAR model with a Poisson likelihood was first fitted to account for spatial heterogeneity, temporal dependence, and environmental effects. The model revealed substantial residual spatial heterogeneity and temporal dependence, whereas spatial dependence was relatively weak. NDVI and NDWI showed negative posterior mean associations with DHF incidence; however, their 95% credible intervals included zero. Residual temporal analysis was subsequently performed to determine whether additional temporal structure remained after ST-CAR estimation. Among the candidate seasonal models, SARIMA (0,0,0) (1,0,0)6 produced the lowest AIC, AICc and BIC, indicating residual temporal dependence at a six-month seasonal lag. Incorporating this residual component into the ST-CAR predictions reduced the RMSE from 1.533081 to 1.533053, corresponding to an improvement of only approximately 0.0018%. Thus, the hybrid model provided negligible improvement in overall point-prediction accuracy, suggesting that the ST-CAR component had already captured most of the systematic spatio-temporal variation in DHF incidence. Nevertheless, the SARIMA component provided additional characterization of residual six-month temporal dependence. Overall, the proposed framework demonstrates the utility of combining Bayesian spatio-temporal modeling, remote-sensing covariates, and residual seasonal time-series analysis to distinguish dominant spatio-temporal variation from secondary residual temporal structure in dengue incidence.
Co-Authors A. Muh. Fiqri La Ali Akbar Ahmar, Ansari Saleh Alfairus, Muh. Qodri Amra Ariyani Andi Nurul Tenriwali Hasanuddin Andi Reski Nurhikmah Andika Saputra Annas, Suwardi Asrini Aswi, Aswi BQ Nurkhalishah K. Damas Gianlugi Alrizqi Etti Herawati Fadhil Rochbini Faisal Faisal Hardianti Hafid Hasna Hasna Indy Pratiwi HR Maghfirah Azis Mahmuddin Mahmuddin Ma’rufi Mildayanti Mildayanti Muh. Imam Shadiq Muh. Irshan Sachrir Sachrir Muhammad Ilyas Muhammad Nur Alam Muhammad Syarifuddin Rahman Nensilianti Nensilianti Nur Salsabila Wero Nurhikma Nurul Aulya Bakri Nurul Haeriyah Ridwan Rabiatul Adawiah Rachmat Hidayat Bachtiar Rahma Agustini Putri Rahmadinar Kadir Rahmat H. S. Rezki Nurfadillah T Rhabjel Aulii Idham Baso Rika Saniarti Riska Cahyani Ruliana Salma Samputri Saslim Sifriyani Siti Nardiyah Muhrami Sitti Masyitah Meliyana R. Sitti Rahma Yunus Sudarmin Sukarna Sukarna Syamsuddin Mas'ud Syamsuddin Mas’ud Syarifuddin Dollah Wanda Yudi Yulia Yulia Yulnita Muchtar Yusuf Ramadana Zakiyah Mar&#039;ah