K-Means Clustering Analysis pada PersebaranTingkat Pengangguran Kabupaten/Kota di Sulawesi Selatan
Akramunnisa Akramunnisa, Fajriani Fajriani · Jurnal Varian · 2020
This study aims to determine the distribution of districts in South Sulawesi based on unemployment rate using clustering analysis. The unemployment rate indicators are districts minimum wage (UMK) and human development index growth rate (IPM). The algorithm used in this study is k-means clustering. The results of k-means clustering analysis showed that of 24 districts in South Sulawesi are divided into two clusters, namely the high and low unemployment rate. The high employment rate cluster consists of 6 districts, namely Pangkep, Sidrap, Luwu Timur, Palopo, Parepare, and Makassar. The rest, 18 districts are in the low employment rate cluster.