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All Journal Media Statistika SAINSMAT Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal Ekonomi Pembangunan STIE Muhammadiyah Palopo Jurnal Matematika Sains dan Teknologi Indonesian Journal of Applied Statistics Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) MATAPPA: Jurnal Pengabdian Kepada Masyarakat M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Varian Inferensi ESTIMASI: Journal of Statistics and Its Application Jurnal Statistika dan Matematika (Statmat) Variansi : Journal of Statistics and Its Application on Teaching and Research Jurnal Statistika dan Aplikasinya ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Amaliah: Jurnal Pengabdian Masyarakat Journal Nursing Care Jurusan Keperawatan Politeknik Kesehatan Gorontalo SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam VARIANSI: Journal of Statistics and Its Application on Teaching and Research Indonesian Journal of Fundamental Sciences Seminar Nasional Hasil Penelitian LP2M UNM SMART: Jurnal Pengabdian Kepada Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Statistics and Its Applications
Aswi, Aswi
Department Of Statistics, Universitas Negeri Makassar
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Bayesian Spatio Temporal Car Localized Model For Mapping The Relative Risk Of AIDS In South Sulawesi Province Taufik, Andi Gagah Palarungi; Aswi, Aswi; Annas, Suwarni
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142776802025

Abstract

Acquired Immune Deficiency Syndrome (AIDS) remains a major public health issue in Indonesia, with South Sulawesi showing a marked rise in cases from 2022 to 2024. This study aims to estimate and visualize the relative risk of AIDS across 24 districts and municipalities in the province by incorporating population density as a spatial covariate. Data were obtained from the Central Bureau of Statistics (BPS) and the South Sulawesi Provincial Health Office. A Bayesian Localised Conditional Autoregressive (CAR) spatio-temporal framework was applied to account for both spatial dependence and temporal variation. Model selection was guided by the Deviance Information Criterion (DIC) and the Watanabe–Akaike Information Criterion (WAIC), with the best-fitting model identified at G = 3 using an Inverse-Gamma (1; 0.01) prior. The analysis revealed that population density had a significant positive association with AIDS incidence. Areas with higher density exhibited elevated relative risk values, particularly Makassar City (RR = 1.95) and Gowa Regency (RR = 1.82), whereas the lowest risks were found in Selayar (RR = 0.41) and East Luwu (RR = 0.45). These findings indicate distinct spatial clustering patterns and underscore the need for geographically focused intervention policies.
Comparison Of Bayesian Spatial Car Models For Estimating The Risk Of Diarrhea Cases In Makassar City Bakri, Nurul Aulya; Yudi, Wanda; Aswi, Aswi; Hidayat, Rahmat
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142774752025

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.Keywords: Bayesian spasial models, CAR BYM, CAR Leroux, Diarrhea, Relative risk.
Bayesian Spatio Temporal Car Localized Model For Mapping The Relative Risk Of AIDS In South Sulawesi Province Taufik, Andi Gagah Palarungi; Aswi, Aswi; Annas, Suwarni
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142776802025

Abstract

Acquired Immune Deficiency Syndrome (AIDS) remains a major public health issue in Indonesia, with South Sulawesi showing a marked rise in cases from 2022 to 2024. This study aims to estimate and visualize the relative risk of AIDS across 24 districts and municipalities in the province by incorporating population density as a spatial covariate. Data were obtained from the Central Bureau of Statistics (BPS) and the South Sulawesi Provincial Health Office. A Bayesian Localised Conditional Autoregressive (CAR) spatio-temporal framework was applied to account for both spatial dependence and temporal variation. Model selection was guided by the Deviance Information Criterion (DIC) and the Watanabe–Akaike Information Criterion (WAIC), with the best-fitting model identified at G = 3 using an Inverse-Gamma (1; 0.01) prior. The analysis revealed that population density had a significant positive association with AIDS incidence. Areas with higher density exhibited elevated relative risk values, particularly Makassar City (RR = 1.95) and Gowa Regency (RR = 1.82), whereas the lowest risks were found in Selayar (RR = 0.41) and East Luwu (RR = 0.45). These findings indicate distinct spatial clustering patterns and underscore the need for geographically focused intervention policies.
Statistika Kategorik untuk Siswa: Meningkatkan Ketajaman Analisis dalam Karya Tulis Ilmiah Aswi, Aswi; Tiro, Muhammad Arif; Poerwanto, Bobby; Ikhwana, Nur; Rais, Zulkifli; Abidin, Muh. Zulkifli
SMART: Jurnal Pengabdian Kepada Masyarakat Vol 5, No 2 (2025): Oktober
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/smart.v5i2.77214

Abstract

Tujuan dari kegiatan ini adalah untuk meningkatkan kamampuan analisis data guru dan siswa SMAN 7 Takalar khususnya dalam mengolah dan menganalisis data kualitatif atau kategorik dalam menyusun karya tulis ilmiah. Kegiatan ini diikuti oleh 18 orang siswa. Pelaksanaan kegiatan ini dimulai dari observasi, identifikasi kebutuhan, pelatihan, pendampingan, serta monitoring dan evaluasi. Hasil dari kegiatan ini adalah peningkatan pengetahuan dan keterampilan pada topik yang dibahas. Selain itu, sekitar 83,33% peserta merasakan pengetahuan dan keterampilannya meningkat secara signifikan. Artinya kegiatan yang dilakukan memberikan dampak kepada peserta sehingga setelah narasumber meninggalkan lokasi kegiatan terjadi sharing ilmu antar peserta sehingga peserta yang belum banyak berkembang juga dapat memahami dan mengimplementasikan materi yang telah diberikan. Peningkatan keterampilan ini diharapkan dapat membantu siswa dalam penyusunan karya tulis ilmiah.
Pendekatan Regresi Nonparametrik Spline Truncated untuk Mengidentifikasi Determinan Angka Kematian Ibu di Indonesia Hidayat, Rahmat; Annas, Suwardi; Aswi, Aswi; Putri, Siti Choiratun Aisyah; Vivianti, Vivianti
Indonesian Journal of Fundamental Sciences Vol 11, No 2 (2025)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/ijfs.v11i2.77643

Abstract

Kualitas kesehatan maternal di suatu negara umumnya diukur melalui indikator utama berupa Angka Kematian Ibu (AKI). Penelitian ini menganalisis pengaruh tiga faktor penting terhadap AKI di Indonesia, yaitu persentase perempuan usia 15–49 tahun yang pernah menikah dan memiliki anak hidup, persentase rumah tangga dengan akses sanitasi layak, serta rata-rata lama sekolah. Untuk mengidentifikasi pola hubungan nonlinier antara variabel-variabel tersebut yang tidak dapat dijelaskan secara optimal oleh model regresi parametrik, digunakan pendekatan regresi nonparametrik Spline Truncated. Model ini mampu menangani data dengan pola acak. Hasil estimasi menunjukkan bahwa model terbaik diperoleh dengan nilai Generalized Cross Validation (GCV) minimum sebesar 1,023 dan koefisien determinasi (R²) sebesar 0,9012. Temuan ini mengindikasikan bahwa ketiga variabel prediktor berpengaruh signifikan terhadap AKI dengan bentuk hubungan yang tidak sepenuhnya linier. Hasil penelitian diharapkan dapat menjadi dasar dalam perumusan kebijakan kesehatan yang lebih efektif dan berbasis data untuk menekan angka kematian ibu di Indonesia
Evaluasi Performa Model Regresi Poisson Tweedie dan Conway Maxwell Poisson dalam Menangani Masalah Dispersi: Studi Angka Kematian Ibu di Provinsi Sulawesi Selatan Aswi, Aswi; Sanusi, Wahidah; Tiro, Muhammad Arif; Sukarna, Sukarna; Haekal, Muh. Fahri; Palarungi, Andi Gagah; Putri, Siti Choirotun Aisyah; Oktaviana, Oktaviana
Indonesian Journal of Fundamental Sciences Vol 11, No 2 (2025)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/ijfs.v11i2.77506

Abstract

Model regresi Poisson digunakan untuk menganalisis hubungan antara satu atau lebih variabel independen dengan variabel dependen berupa data cacahan. Salah satu asumsi utamanya adalah kesamaan antara nilai mean dan variansi (equidispersi). Namun, dalam praktiknya, asumsi tersebut sering tidak terpenuhi. Kondisi ini menyebabkan model regresi Poisson kurang sesuai digunakan, karena dapat menghasilkan estimasi standar error yang terlalu kecil (underestimate). Model alternatif yang dapat digunakan untuk mengatasi masalah overdispersi adalah Regresi Poisson Tweedie dan Conway Maxwell Poisson (CMP). Penelitian ini bertujuan untuk mengevaluasi kinerja model regresi Poisson Tweedie dan regresi CMP dalam menangani masalah dispersi pada data Angka Kematian Ibu (AKI) di Provinsi Sulawesi Selatan, Indonesia. Estimasi parameter dilakukan dengan metode Estimasi Kemungkinan Maksimum (MLE), sedangkan kinerja model dinilai berdasarkan Akaike Information Criterion (AIC), Mean Square Error (MSE), dan signifikansi parameter. Hasil penelitian menunjukkan bahwa model regresi Poisson standar kurang sesuai karena adanya pelanggaran asumsi ekuidispersi. Sebaliknya, model CMP dan Poisson Tweedie memberikan alternatif yang lebih tepat, dimana Model CMP menunjukkan akurasi prediktif yang lebih tinggi dengan nilai MSE terendah. Faktor perdarahan, hipertensi, gangguan kardiovaskular, dan komplikasi pasca-aborsi ditemukan memiliki pengaruh yang signifikan terhadap kematian ibu, sementara infeksi tidak signifikan secara statistik. 
The Application of the K-Medoid Classification Method for Analyzing Crime Rates in South Sulawesi Annas, Suwardi; Aswi, Aswi; Irwan, Irwan
Inferensi Vol 8, No 3 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i3.21464

Abstract

This research employs the k-medoid clustering method to analyze districts and cities in South Sulawesi based on their crime rates. As the population grows, employment opportunities tend to diminish, which can increase stress levels and, consequently, the likelihood of criminal behavior. To evaluate the distribution of criminal incidents across South Sulawesi, the k-medoid method is used to cluster regions. Unlike other clustering methods, k-medoid utilizes the median as the cluster center (medoid), which enhances its robustness against outliers. Specifically, the Partitioning Around Medoids (PAM) algorithm is applied, where initial objects are randomly selected to represent clusters. If the error value is high, the cluster centers are adjusted until the error is minimized. The dataset comprises crime incidence data for South Sulawesi in 2020, focusing on various types of crime. The analysis identified an optimal number of three clusters based on the Silhouette coefficient. Cluster 1 includes 11 regions, Cluster 2 consists of 8 regions, and Cluster 3 contains 5 regions. These clusters provide a comprehensive overview of the crime conditions across different regions within each cluster.
Bayesian Spatio-Temporal Conditional Autoregressive Modelling of Factors Affecting Pneumonia Cases in Indonesia Risma Mastory; Aswi, Aswi; Muhammad Fahmuddin; Lalu Ramzy Rahmanda
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.56315

Abstract

The Bayesian Spatio-Temporal Conditional Autoregressive (BST CAR) method is a statistical approach used to analyze data with both spatial and temporal components. While the BST CAR model has been widely applied in various studies, no research has yet explored using the Localized BST CAR model for pneumonia cases in Indonesia. This study aims to identify and model the factors influencing pneumonia incidence in Indonesia using the Localized BST CAR framework. The data analyzed in this study consist of the number of pneumonia cases in Indonesia from 2018 to 2022, along with variables believed to affect the incidence. The findings indicate that the Localized BST CAR model with G=3 provides the best fit for modeling the relative risk of pneumonia cases in Indonesia. Key factors found to significantly influence pneumonia cases include the percentage of exclusively breastfed infants, the percentage of infants with complete basic immunization, and the percentage of the population living in poverty. Notably, the percentage of exclusively breastfed infants and the percentage of fully immunized infants were positively associated with pneumonia cases, while the percentage of the poor population had a negative effect
Application of the Mixed Geographically Weighted Regression Model to Identify Influencing Factors for Literacy Development Index of Indonesian Society's in 2022 Zulhijrah Zulhijrah; Ruliana Ruliana; Aswi Aswi
Indonesian Journal of Applied Statistics Vol 7, No 2 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v7i2.88784

Abstract

The mixed geographically weighted regression (MGWR) method is a combination of a linear regression model and a geographically weighted regression (GWR) model. The MGWR model can produce parameter estimates that have global parameter estimates, and other parameters that have local parameters according to the observation location. This method can be used in epidemiological studies that are influenced by spatial heterogeneity. The aim of this research is to determine and model the factors that influence the Community Literacy Development Index (CLDI) in Indonesia based on MGWR modeling. The data used in this research is CLDI data in Indonesia in 2022 along with the factors that are thought to influence it. The results of this research indicate that the MGWR model outperforms both the linear regression and GWR models, as it yields the lowest Akaike information criterion (AIC) value and an ?² value of 96.54%. Based on the modeling results, several factors influencing CLDI were identified, including the percentage of libraries, the adequacy ratio of library collections, the average length of schooling, and the level of participation in organized learning. Keywords: Literacy; literacy development index; mixed geographically weighted regression; spatial
Determinants of Maternal Mortality in Indonesia: A B-Spline Nonparametric Regression Approach to Identify Nonlinear Relationship Patterns Annas, Suwardi; Aswi, Aswi; Hidayat, Rahmat
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 11 No. 1 (2026): Mathline : Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v11i1.1015

Abstract

Maternal health quality is commonly assessed using the Maternal Mortality Ratio (MMR), which remains relatively high in Indonesia compared to regional and global targets. Understanding the determinants of MMR is therefore crucial for effective health policy formulation. This study aims to analyze the influence of three key factors on MMR in Indonesia: the percentage of women aged 15–49 who have ever been married and given birth to a live child, the percentage of households with access to proper sanitation, and the average years of schooling. To capture potential nonlinear relationships that may not be adequately addressed by conventional parametric regression models, this study employs a nonparametric B-spline regression approach. The analysis was conducted using the R statistical software. Model selection was based on the Generalized Cross-Validation (GCV) criterion to determine the optimal spline configuration. The results show that the optimal model achieves a minimum GCV value of 0.108 and an R² value of 0.8981, indicating a strong explanatory power and excellent model fit. The findings reveal that all three predictor variables have a significant and nonlinear effect on MMR. These results highlight the importance of considering flexible modeling approaches in maternal health studies and provide empirical evidence to support the development of more targeted and effective policies aimed at reducing maternal mortality in Indonesia.
Co-Authors A. Nurul Amalia AA Sudharmawan, AA Abdul Rahman Abdul Rahmat Abidin, Muh. Zulkifli Abidin, Muhammad Rais Ahmar, Ansari Saleh Aidid, Muhammad Kasim Aisyah Putri , Siti Choirotun Ambo Upe Andi Feriansyah Andi Feriansyah Andi Gagah Palarungi Taufik Andi Gagah Palarungi Taufik Andi Muhammad Ridho Yusuf Sainon Andin P Andi Shahifah Muthahharah Ankaz As Sikib Annas, Suwardi Annas, Suwardi Annas, Suwardi Annas, Suwarni Aprilia Wardani Syam , Dewi Arbianingsih Asrirawan Assagaf, Said Fachry Awaluddin Awaluddin Awi Awi Awi Dassa, Awi Awi, Awi Bakri, Nurul Aulya Besse Sulfiani Bobby Poerwanto Bobby Poerwanto Bobby Poerwanto Bustan, Muhammad Nadjib Cramb, Susanna Diana Eka Pratiwi Eka Hadrayani Fahmuddin, Muhammad Fahmuddin, Muhammad Fajar Arwadi Folorunso, Serifat Adedamola Haekal, Muh. Fahri Halimah Husain Hammado, Nurussyariah Herman, Nur Taj Alya’ Hidayat , Rahmat Hisyam Ihsan Huriati, Huriati Idul Fitri Abdullah Ikhwana, Nur Irwan Irwan Irwan, Irwan Ishma Azizah S Isnaini, Mardatunnisa Isnaini, Wulan Maulia Kaito, Nurlaila Lalu Ramzy Rahmanda M Nadjib Bustan M. Miftach Fakhri Mahadtir, Muhamad Mangkona, Andi Ilham Azhar Mar'ah, Zakiyah Mardatunnisa Isnaini Mauliyana, Andi Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Ammar Naufal Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Arif Tiro, Muhammad Arif Muhammad Fahmuddin Muhammad Fahmuddin Muhammad Fahmuddin Sudding Muhammad Kasim Aidid Muttaqin, Imam Akbar Natalia, Derliani Nini Harnikayani Hasa Novianti, Andi Rima Nur Aziza S Nurhikmawati, Nurhikmawati Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurhilaliyah Nurhilaliyah, Nurhilaliyah Nurkaila Kaito Nurlia Nurlia Nurul Fadilah Syahrul Nurul Ilmi Nurwan, Nurwan Nusrang, Muhammad Oktaviana Oktaviana Oktaviana Oktaviana Palarungi, Andi Gagah Panessai Sir Poerwanto, Bobby Poerwanto, Bobby Poewanto, Bobby Putri Ananda, Elma Yulia Putri, Siti Choiratun Aisyah Putri, Siti Choirotun Aisyah Rahma, Ina Rahman, Abdul Rahmat Hidayat Rahmat Hidayat Rahmawati Rahmawati Rahmawati Rais, Zulkifli Ramadani, Reski Aulia Rezki Amalia Idrus Riska Saputri Risma Mastory Ruliana Ruliana Ruliana Ruliana Ruliana Ruliana Ruliana Ruliana, Ruliana S, Muhammad Fahmuddin Sahlan Sidjara Saleh, Andi Rahmat Salsabila, Afifah Sapriani Shanty, Meyrna Vidya Siti Choirotun Aisyah Putri Sitti Aminah Sri Ayu Astuti Sri Rahayu Stevani Stevani Suardi, Shafira Suci Amaliah Sudarmin Sudarmin Sudarmin Sudarmin Sudarmin Sudarmin Sudarmin Sudarmin Sukarna Sukarna Sukarna Sukarna Sukarna Sukarna Sukarna Sukarna Sukarna Sukarna, Sukarna Sulistiawaty Sulistiawaty, Sulistiawaty Sumarni Sumarni Supriadi Yusuf Susanna Cramb Suwardi Annas Suwardi Annas Syafruddin Side Syamsiar, Syamsiar Taufik, Andi Gagah Palarungi Vivianti Vivianti Vivianti Wahidah Sanusi Wea, Maria Dominggo Yassar, La Ode Salman Yudi, Wanda Yunus, Sitti Rahma Zulhijrah Zulhijrah Zulhijrah Zulhijrah Zulhijrah Zulkifli Rais