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All Journal Journal of Mathematics, Computation and Statistics (JMATHCOS) Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam
Nurul Aulya Bakri
Universitas Negeri Makassar
Mathematics

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Mixed Geographically Weighted Regression Modeling Of Childhood Pneumonia Cases In West Java Province  Abdul M. Achmad; Aswi Aswi; Siti Choirotun Aisyah Putri; Nurul Aulya Bakri; Wanda Yudi; Rahmawati
SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Vol. 15 No. 1 (2026): Volume 15 Nomor 1 (Maret 2026)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/j60rfb72

Abstract

Pneumonia is one of the leading causes of morbidity and mortality among children under five in Indonesia, including in West Java Province, which records the highest number of childhood pneumonia cases nationally. The spatial variation in pneumonia incidence indicates substantial heterogeneity across regions that cannot be adequately captured by global regression models. This study aims to analyze the factors influencing the number of pneumonia cases among children under five in West Java in 2024 using the Mixed Geographically Weighted Regression (MGWR) approach. Data were obtained from the West Java Provincial Health Office and Statistics Indonesia (BPS), comprising the number of pneumonia cases and predictor variables including exclusive breastfeeding coverage, poverty rate, percentage of low birth weight (LBW) infants, PHBS (clean and healthy living behavior), complete basic immunization coverage, and adequate housing. The global linear regression results show that not all variables have significant effects, and the model fails to adequately capture data variation, with indications of heteroskedasticity—thereby necessitating a spatial modeling approach. While the GWR model identifies local variation, model comparison demonstrates that the MGWR model performs best, yielding a lower AIC value (474.46) and a higher coefficient of determination (69.83%) than both GWR and the global model. MGWR identifies LBW and immunization coverage as global variables with consistent effects across all areas, whereas exclusive breastfeeding, PHBS, poverty, and adequate housing exhibit spatially varying influences. Cluster analysis using MGWR identifies five regional groups, each reflecting distinct determinants of childhood pneumonia in West Java. These findings highlight that public health interventions aimed at reducing childhood pneumonia must incorporate local spatial conditions, and MGWR provides a more appropriate analytical approach than global regression models.
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.
Application of Geographically and Temporally Weighted Regression to Under-Five Diarrhea Cases in East Java Nurul Aulya Bakri; Suwardi Annas; Aswi Aswi
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/rdfs5k14

Abstract

Under-five diarrhea remains an important indicator of environmental health conditions. In East Java Province, Indonesia, the incidence varies across districts and over time, indicating spatial dependence and temporal dynamics. This study aims to analyse spatial–temporal variation and examine the influence of environmental, health, and sociodemographic factors using the Geographically and Temporally Weighted Regression (GTWR) approach. Spatial panel data from 38 districts/cities during 2019–2023 were analysed, including variables on exclusive breastfeeding, sanitation, vitamin A, immunisation, drinking water facilities, and population density. Moran’s I and heterogeneity tests were applied, followed by GTWR estimation using adaptive space–time weighting. The results reveal significant spatial autocorrelation and heterogeneity, with variable effects differing across regions and periods. Vitamin A supplementation and population density show consistent positive associations, while safe drinking water exhibits a protective effect. GTWR outperforms multiple linear regression, as indicated by lower AIC and higher R² values. In conclusion, GTWR provides a more accurate representation of diarrhea patterns. It is recommended that interventions be tailored to local conditions by considering spatial and temporal variations.
Co-Authors Abdul M. Achmad Annas, Suwardi Aswi Aswi Aswi, Aswi Rahmat Hidayat Rahmawati Siti Choirotun Aisyah Putri Wanda Yudi