Perbandingan Metode C-Means dan Fuzzy C-Means Pada Pengelompokan Kabupaten/Kota Di Kalimantan Berdasarkan Indikator IPM Tahun 2019

Abstract

The Human Development Index is an indicator used to measure one important aspect related to the quality of the results of economic development, namely the degree of human development. Data Mining is a technique or process for obtained information from large database warehouses. Based on its function, one of the data mining tasks was to group data, where the method used in this study was the C-Means and Fuzzy C-Means grouping methods. The two classification methods were applied to the human development index indicator data. The purpose of this study was to determined the best method based on the ratio of the standard deviation in clusters to the standard deviation between clusters. Based on the results of the analysis, it was concluded that the best method is the C-Means method with the value of the standard deviation value in the cluster against the standard deviation between clusters of 0.434 which results in 5 clusters, namely cluster 1 consisting of 9 districts / cities, cluster 2 consisting of 7 districts / cities, cluster 3 consists of 10 districts / cities, cluster 4 consists of 15 districts / cities and cluster 5 consists of 15 districts / cities.