Identifikasi Prediktor Jumlah Kasus Baru Tuberkolosis di Jawa Barat: Perbandingan Regresi Poisson, Binomial Negatif, dan Poisson terbobot Geografis - Khalishah, Athayya Putri; Advani, Nadjma Maulidya; Syahputra, Fathur Rahman; Brilliant, Indira Ihnu; Setiawan, Ezra Putranda (ESTIMASI: Journal of Statistics and Its Application, 2026)
Tuberculosis (TB) is still a serious problem for the world, including Indonesia as the third largest contributor of TB cases in the world. This study aims to analyze the factors that affect the number of new TB cases in West Java Province as the province with the most TB cases in Indonesia in 2022. The response variable used is the number of new TB cases in West Java Province in 2022, while the predictor variables used are population density, number of AIDS cases, poverty, and sanitation. Since the dependent variable comes from counting procedure, we conducted the analysis through three models, namely Poisson regression, negative binomial regression, and Geographically Weighted Poisson Regression (GWPR). We find that in the negative binomial method there was only one insignificant predictor variable, namely population density. Based on influential predictor variables, GWPR models in districts / cities in West Java can be separated into four groups. The best model to analyze the factors affecting new TB cases is the negative binomial regression model with an AIC of 487.76.