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Journal : VARIANSI: Journal of Statistics and Its Application on Teaching and Research

GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION (GWNBR) IN MODELING THE RISK FACTORS OF PNEUMONIA DISEASE AMONG TODDLERS IN THE CENTRAL SULAWESI PROVINCE Mar'ah, Zakiyah; Rais, Zulkifli; Haris, A. Sulfiana
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 03 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm151

Abstract

This research was conducted to map and model the number of Pneumonia cases in Central Sulawesi Province using the Geographically Weighted Negative Binomial Regression (GWNBR) approach. The data used were Pneumonia case data in Central Sulawesi Province obtained from the Health Publication of Central Sulawesi Province in 2021. The analysis results with the GWNBR method indicated that predictor variables significantly influencing the number of Pneumonia cases in each district/city of Central Sulawesi Province were Exclusive Breastfeeding Percentage (X1), Complete Basic Immunization Percentage (X2), Percentage of Toddlers Receiving Vitamin A (X3), and Percentage of Coverage of Toddler Services (X5). Meanwhile, the variable Low Birth Weight (X4) does not significantly affect the cases.