Java Island Health Profile Clustering using K-Means Data Mining

Abstract

Health is the best gift in life, because with health humans can carry out daily activities. Administratively, Java Island consists of 85 administrative regions and 34 cities. Therefore, it is very important to understand the health level of each area. The main objective of this research is to divide each region (district and city) into several groups and use the K-means method to determine health status based on 8 data parameters into certain groups. Algorithm in groups, will place the data based on the similarity of characteristics between groups. The results showed that there were 4 clusters of health profiles in Java, with 1 high health quality cluster in Central Jakarta, 55 regencies/municipalities with low health quality, 52 regencies/cities with low health quality. and the quality of health is quite low there are 13 districts/cities, it can be concluded that the health indicators in Java