Pemodelan Jumlah Kasus Tuberkulosis pada Anak di Kota Bandung dengan Pendekatan Geographically Weighted Negative Binomial Regression

Brenda Bunga Prasenda (Universitas Airlangga, Indonesia)
Mohamad David Hermawan (Universitas Airlangga, Indonesia)
Mutiara Aisharezka (Universitas Airlangga, Indonesia)
Sufyan Ats Tsauri (Universitas Airlangga, Indonesia)
Nur Chamidah (Universitas Airlangga, Indonesia)

G-Tech : Jurnal Teknologi Terapan
Vol 8 No 1 (2024): G-Tech, Vol. 8 No. 1 Januari 2024

Tuberculosis (TB) is an infectious disease. According to WHO (2020), 1.5 million people die from tuberculosis and it is also the 13th largest cause of death in the world and the second largest infectious disease cause of death after COVID-19. This research aims to create a new model based on different methods, targets and time to determine the modeling of factors that influence the number of tuberculosis diseases in Bandung City using the Geographically Weight Negative Binomial Regression (GWNBR) method. The modeling in this study is known to have differences between Negative Binomial Regression and Geographically Weight Negative Binomial Regression (GWNBR) with Bojongloa Kaler having the highest cases, significantly influenced by the number of cases in adult men. This research encourages the Bandung City government to provide equitable health services, consider these factors, and evaluate policies to reduce tuberculosis cases in children aged 0-14 years, especially in adult males.