Penerapan Algoritma Klasifikasi C-Means Klustering Pada Segmentasi Vaksinasi Meningitis Pada Wilayah Tapal Kuda Di Jawa Timur

Abstract

One important metric for evaluating the standard of living in a place is community welfare. The purpose of this study is to use the C-Means algorithm to group areas in East Java's horseshoe region according to welfare metrics. Vaccination is a key strategy to stop the spread of meningitis. By gathering information from medical facilities that run immunization campaigns, the Tapal Kuda regional administration keeps track of vaccine successes. The data is then gathered, processed, and made public by the local government. Since it is challenging for each sub-district to ascertain whether or not they have reached their vaccination targets, the lack of a classification of vaccination accomplishment data at the sub-district level is thought to be less effective. In order to categorize the attainment of vaccination targets in each region in Tapal Kuda, East Java, we employ the C-Means Clustering technique to group data according to similarities. Maps are used to display the classification's outcomes. This mapping is made possible by a web-based Geographic Information System (GIS). According to the study, data regarding the area's progress toward meningitis vaccination targets can be sorted using the C-Means Clustering algorithm in the WebGIS-based Geographic Information System for Meningitis Vaccination Achievement in the Horseshoe area. Five of the six districts in the Rurar Area region have achieved the goal, according to the findings of C-Means iteration calculations.