Cluster Analysis of Indonesian Provinces Based on Health Performance Indicators Using Fuzzy C-Means

Abstrak

Based on the Sustainable Development Goals (SDGs), especially the third goal which focuses on ensuring a healthy life and improving the welfare of all residents in all age groups, from infants to the elderly, it is closely related to looking at existing health indicators. The Indonesian region consisting of 34 provinces makes policies difficult to generalize due to the different characteristics of each region. So a cluster method is needed where regional objects will be clustered into several groups so that policies will be better implemented in a formed cluster. One clustering method that can be used is Fuzzy C-Means. FCM provides a membership value in the form of degrees between 0 and 1 which indicates how strong the relationship of a data with each group, from the results of the analysis using FCM obtained the results of the formation of 2 clusters which illustrate that cluster 1 is a cluster with indications of areas that have good health, and cluster 2 is a cluster with indications of poor, cluster 1 consists of 12 provinces and cluster 2 consists of 22 provinces.