<![CDATA[Indonesia aimed to eliminate Tuberculosis (TB) by 2050, with efforts scheduled to begin in 2030. However, TB cases remained high in Kuningan Regency, necessitating urgent measures to address this issue. This research employed a Geographic Information System (GIS) approach to map TB cases, helping to understand the distribution patterns of patients. This information guided the development of effective policies to address TB cases from an epidemiological perspective. Methods. In this non-reactive research design, the study focused on 32 sub-districts in Kuningan Regency, which included a total of 937 tuberculosis (TB) patients. The variables analyzed included the number of TB cases, case notification rate (CNR), total population, population density, the presence of private practice doctors, and the number of traders. Descriptive data analysis was conducted to create maps, along with spatial data analysis using Moran's Index through GeoDa software. Results. Spatial analysis using Geoda found spatial autocorrelation between the number of TB cases and population density, the availability of private practice doctors, and the number of trade workers. The Z scores of these four variables were quite large and >Z0.95, so the distribution pattern of TB sufferers was declared to be a group (cluster). Conclusion. sed on the mapping of TB sufferers and spatial analysis, it was determined that the distribution pattern of TB sufferers in Kuningan Regency formed a cluster pattern, and there was an autocorrelation relationship between population density, the availability of private practice doctors, and the number of traders with TB sufferers. It was hoped that the results of this research would serve as material for improving TB interventions.]]>
