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

Dhika Alfatah (Sekolah Tinggi Ilmu Administrasi Bengkulu)

Jurnal Komputer, Informasi dan Teknologi
Vol. 1 No. 2 (2021): Desember

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..