Pemodelan Kejadian Penyakit Tuberkulosis di Provinsi Jawa Barat Tahun 2023 Menggunakan Metode Geographically Weighted Negative Binomial Regression (GWNBR)

Abstract

Tuberculosis (TB) is the leading cause of death due to infection by the bacteria Mycobacterium tuberculosis, which can attack the lungs and other organs. Reducing TB rates is one of the main targets in the Sustainable Development Goals (SDGs). In 2023, Indonesia will be ranked second in the world for TB cases after India, with West Java Province as one of the main contributors experiencing a significant increase, namely 160,966 cases in the productive age group (≥15 years) and 50,993 cases in the children's group (0–14 years). This study aims to analyze the factors that influence the number of TB cases in West Java Province in the productive age group using the Geographically Weighted Negative Binomial Regression (GWNBR) method, which considers spatial aspects between regions and is able to handle overdispersion problems in count data. The six independent variables tested include population density, percentage of public places that meet health requirements, number of hospitals, percentage of the population who smoke, air quality index, and number of HIV sufferers. The modeling results using the GWNBR method with Fixed Kernel Gaussian weighting produced ten regional groups, each with different risk factor characteristics for the number of TB cases.