Clustering of Social Conditions in Batam, Indonesia Using K-Means Algorithm and Geographic Information System
Dwi Ely Kurniawan, Agus Fatulloh · 2018
Batam is an archipelago that has different social characteristics of each sub-district. Social problems should be a concern and responsibility of both the public and government. For the programs launched by the government in accordance targeted and it is necessary to determine the priorities of the social problems that arise in each region. This study uses k-means algorithm to classify social problems in the form of clusters. Each group has the same characteristics in the group while the other cluster to form the next group according to their characteristics. The results of the study, a k-means algorithm determines the group and map the distribution of social issues into the Geographic Information System (GIS) to facilitate the social information to know each district and identify priorities for help to the government program on target.