Pemetaan Risiko Penyakit Tuberkulosis (TBC) di Kota Surakarta dengan Spatial Empirical Bayes

Abstract

Tuberculosis is an infectious disease that can attack human with a poor immune system. In 2017, there were 723 residents of Surakarta tested positive for tuberculosis. The spatial empirical Bayes method is a good method for mapping the risk of tuberculosis because this method includes spatial dependency information and can overcome small area problems. This method can help the prevention of tuberculosis in Surakarta. In the analysis, it was found that the number of cases of tuberculosis in Surakarta has a spatial dependency that has an impact of the spread of tuberculosis. Sub-district classification with the highest risk value is Jebres, Tegalharjo, Jajar, Laweyan, Sondakan, Purwosari, Mangkubumen, Keratonan, Timuran, and Punggawan. Keywords : tuberculosis, mapping, spatial empirical Bayes, Surakarta