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All Journal Unisda Journal of Mathematics and Computer Science (UJMC)
Preti Elvina Septilita
Universitas Jenderal Soedirman
Computer Science & IT Education Mathematics

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Perbandingan Model Generalized Poisson Regression dan Regresi Binomial Negatif pada Jumlah Kasus Pneumonia Balita di Provinsi Jawa Timur Preti Elvina Septilita; Nunung Nurhayati; Ari Wardayani
UJMC (Unisda Journal of Mathematics and Computer Science) Vol. 12 No. 1 (2026): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department, Faculty of Sciences and Technology Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v12i1.13648

Abstract

Pneumonia in children under five is one of the leading causes of death among children worldwide. In Indonesia, East Java Province ranks seventh in terms of the number of cases of pneumonia in children under five. In 2024, there were 99,048 cases of pneumonia in children under five in the province. The number of cases of pneumonia in children under five is discrete data that often experiences overdispersion, making Poisson regression unsuitable for use. This study aims to compare the Generalized Poisson Regression (GPR) model and negative binomial regression and identify factors that influence cases of pneumonia in children under five in East Java Province. This study uses secondary data on the number of cases of pneumonia in children under five at the district/city level in East Java Province in 2024. Based on the results of the study, it was found that the negative binomial regression model was the best model with an Akaike Information Criterion (AIC) value of 652.37. The factors that had a positive effect were the percentage of infants receiving vitamin A, while the factors that had a negative effect were the percentage of low birth weight infants.
Co-Authors Ari Wardayani, Ari Nunung Nurhayati