Algoritma Metode K-Means untuk Clustering Kabupaten dan Kota di Sumatera Utara Berdasarkan 4 (Empat) Faktor Kemiskinan Tahun 2022

Abstract

Poverty means no possessions and lack of money. The Department of Social Affairs and the Central Bureau of Statistics, defines it as the inability of individuals to meet the minimum basic needs to live a decent life. Poverty can be characterized by a lack of common things such as food, clothing, shelter, and drinking water, which are closely related to the quality of life. This research aims to assist the local government of North Sumatra province in improving services to poor people spread throughout regencies and cities. The data was taken from secondary data from the Central Statistics Agency and processed using the K-means method, where the samples taken were 33 districts and cities in North Sumatra Province. The K-Means method is a method that looks for the optimal group of data by minimizing the criteria of the number of squared errors with an optimal iteration procedure. The results of the district and city clustering research based on 4 poverty factors show that there are 3 cluster divisions, namely cluster 1 with a high poverty rate consisting of 4 cities/districts, cluster 2 with a medium poverty level there are 7 cities/regencies and cluster 3 with a low poverty rate consisting of 22 cities/regencies.