Application of the K-Means Clustering Algorithm in Mapping the Regional Voter Strategy for the Legislative Candidates for the DPR RI

Abstract

This study applies Data Mining by using the Clustering method to map the electoral strategy for the Legislative Candidates in Bengkulu City. The algorithm used is K-Means Clustering, where data grouped based on the same characteristics will be included in the same group and data sets are entered into the same group. in non-overlapping groups. The information displayed is in the form of product data groups based on the voter vote level in each village, so that it is known which regions/villages have high, medium or low voter levels. The test was carried out with the RapidMiner 5.3 application, resulting in clusters with high, medium or low voter rates..