Penerapan Data Mining untuk Klasterisasi Data Anggaran Pendapatan dan Belanja Daerah Menggunakan Algoritma K-Means

Abstract

To continue the development relay and fulfill the transition period until the simultaneous elections are held, it is necessary to prepare a Regional Development Plan (RPD) for regional heads whose terms of office end in 2022. The K-Means algorithm approach can be applied in analyzing the level of potential regional income and expenditure based on regional income and expenditure clusters that have results in the K-Means algorithm testing process, two clusters cluster 1 (C0) is a category of high spending potential consisting of and cluster 2 (C1) and is a low spending potential. The applied K-Means algorithm model has results that show a new insight, namely the grouping of regional income and expenditure budget data for the Tolikara Regency BPKAD based on 2 clusters has cluster results of 47 and 3. In analyzing the level of potential regional income and expenditure, the results of the test have centroid results 1 192973008, 16700000 and centroid results 2 7000000 and 225000000.