Analisis Cluster dengan Metode K-Means untuk Mengelompokkan Kabupaten/Kota di Provinsi Sumatera Utara Berdasarkan Indikator Sosial, Ekonomi, dan Kesehatan Tahun 2022

Abstract

The success of development in each region, the government needs to record and classify which regions still need treatment in the development process. This is viewed from social, economic and health indicators which are in line with the Human Development Index. The science that can be implemented in grouping is cluster analysis. This research will discuss Cluster Analysis of the Human Development Index in North Sumatra Province. Cluster analysis is a technique for grouping objects based on similar characteristics. The aim of this research is to group the HDI in North Sumatra Province based on 9 variables, namely life expectancy (X1), expected length of school (X2), average length of school (X3), real expenditure per capita (X4), level of complaints. Health (X5), infant mortality rate (X6), open unemployment rate (X7), number of poor people (X8), and population (X9). The cluster analysis method used in this research is K-Means. From the analysis results it was found that the grouping of 33 districts/cities in North Sumatra Province could form 4 clusters, namely cluster 1 was dominant over variable X6 which had a total of 5 districts/cities in the low category, cluster 2 was dominant over variable 11 districts/cities in the high category, cluster 3 is dominant over variables X2, members are 15 districts/cities in the medium category. The variables that provide the biggest differences are life expectancy (X1), average years of schooling (X3), real expenditure per capita (X4), infant mortality rate (X6), and population (X9). Regional governments are advised to create programs that are relevant to the problems of each region based on the supporting determinants of each region.