Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal SAINSMAT SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam VARIANSI: Journal of Statistics and Its Application on Teaching and Research
Bakri, Nurul Aulya
Unknown Affiliation
Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Physics

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
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.
Pendekatan Geographically Weighted Regression (GWR) untuk Menganalisis Hubungan PDRB Sektor Pertanian, Kehutanan, dan Perikanan dengan Faktor Pencemaran Lingkungan di Jawa Timur Bakri, Nurul Aulya; Annas, Suwardi; Aidid, Muhammad Kasim
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 01 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm194

Abstract

The Geographically Weighted Regression (GWR) method is a method used to analyze spatial heterogeneity, where the same independent variable gives unequal responses at different locations in a research area. The purpose of this study was to determine the environmental pollution factors that affect GRDP in the agricultural, forestry and fisheries sectors in East Java. The data used in this study are the GRDP of the Agriculture, Forestry and Fisheries sectors in East Java in 2020 along with the environmental pollution factors that are thought to influence it. The results of this study obtained a different model for each district/city. The GWR model shows better results than the multiple linear regression model, as seen from the smallest AIC value and the largest R2
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.
Co-Authors Aidid, Muhammad Kasim Aswi, Aswi Rahmat Hidayat Suwardi Annas Yudi, Wanda