Analysis of district cluster based on the indicator of Gross Regional Domestic Product (GRDP) using unsupervised learning

The economic lameness among regions is an unsolved problem all this time. To determine policies, to plan economic development right on target, and to solve the economic lameness, we need sufficient and accurate data and information. In this research, there’s data of Gross Regional Domestic Product (GRDP) would be analyzed here to get the economic pattern of District cluster in Indonesia. The tool for this analysis in this research is clustering technic in which it has a method called K-Means. K-means groups the obtained data based on its features for each. This research results in cluster 5 as the optimal ones. With the value of DBI 0.9640