SPATIAL CLUSTERING, AUTOCORRELATION, AND HOTSPOT ANALYSIS OF PULMONARY TUBERCULOSIS INCIDENCE IN BANDA ACEH, INDONESIA: Analisis Klaster Spasial, Autokorelasi, dan Hotspot Kejadian Tuberkulosis Paru di Banda Aceh, Indonesia - Mudatsir; Farrah Fahdhienie; Taufik Fuadi Abidin; Nurjannah Nurjannah (Universitas Airlangga, 2026)
Background: Pulmonary tuberculosis (TB) remains one of the most significant fatal infectious diseases, affecting millions of individuals worldwide. Mitigating and managing TB requires identifying risk factors and conducting geographical analysis using Geographic Information System (GIS) methodology. In Banda Aceh, which has a relatively high TB burden in Aceh Province, understanding the spatial distribution of TB is essential for targeted intervention. Purpose: This research aims to examine the geographical patterns (clustering, autocorrelation, and hotspots) of pulmonary TB incidence in Banda Aceh, Indonesia. Methods: An analytical descriptive study of 196 patients with pulmonary tuberculosis was conducted using a GIS approach. Clustering analysis techniques were performed using SatScan, while autocorrelation and hotspot analyses were conducted using GeoDa. Furthermore, the results were visualized geographically using QGIS. Results: The results indicate a Most Likely Cluster located in Meuraxa, Kuta Raja, Kuta Alam, Baiturrahman, Jaya Baru, Banda Raya, and Lueng Bata subdistricts, with a Log Likelihood Ratio (LLR) of 14.12, a Relative Risk (RR) of 2.28, and a clustering radius of 4.71 kilometers. Moran’s I analysis shows a negative value (-0.17), indicating a dispersed pattern. One subdistrict, Meuraxa, was identified as a coldspot (Low category) with a p-value of 0.05. Conclusion: Pulmonary TB incidence in Banda Aceh shows a significant cluster in seven subdistricts, a dispersed pattern (negative Moran’s I), and a Low-category coldspot in Meuraxa, indicating the need for targeted interventions in clustered areas and equitable TB control across regions.