Geoinformatics of tuberculosis (TB) disease in Jakarta city Indonesia

Abstract

Tuberculosis (TB) disease has still become the leading cause of morbidity and mortality in Indonesia. TB had a relationship between human and their environment, especially in an urban area. The urban area had the highest population and density, that is the way the accurate information about the urban environment of the TB area is critical. The research objective to representing characteristic spatial of TB patients lived in Jakarta year 2017. The research used a method using visual interpretation from superimposed spatial data. Spatial data collection from google earth data, household area (RW boundary), and TB patient addressed from the hospital. The total TB patients in Jakarta City year 2017 in total 114 from a hospital and distributed in 108 household areas (RW boundary). The result of geoinformatics of the urban environment, first building population, building density, vegetated covered, and distance from the main road. The TB area characteristic had two classified high and low, based on total patient TB disease in a household area (RW boundary). The research concluded of the geoinformatics of TB disease in Jakarta City year 2017 with highly classified is high building population and building density, lowest vegetated covered (high temperature), and near the main road. The research also uses the PAM algorithm to cluster the patient and resulted in four clusters with differ mostly in building density, building temperature, and the distance to the nearest river.