Optimization of K-Means Clustering with Elbow Method for Identification of TB Prone In Central Java

Abstract

Tuberculosis (TB) is an infectious disease caused by the bacillus Mycobacterium tuberculosis. This infectious disease needs more attention because the transmission rate is still high, especially in areas with high case finding rates and low treatment success rates. This study was conducted to monitor areas prone to TB case transmission, especially areas in Central Java Province. The K-Means method was applied to determine areas prone to TB transmission by considering the success rate of TB treatment, through the Elbow approach to determine the optimal number of clusters. The results of clustering show areas that are classified as vulnerable areas, which are areas with high transmission cases but low treatment success. Visualization of clustering results in scatter plots that clarify the division of areas into clusters and help in identifying treatments and areas that need further intervention.