IMPLEMENTASI FUZZY C-MEAN DAN ALGORITMA PARTICLE SWARM OPTIMIZATION UNTUK CLUSTERING KABUPATEN/KOTA DI INDONESIA BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA

Abstract

This research is aimed to determine conduct clustering in accordance with the conditions of districts / cities throughout Indonesia based on the IPM indicator and to determine the performance comparison of Fuzzy C-Means using particle swarm optimization compared to ordinary fuzzy c mean. The study uses 514 district / city data in Indonesia based on four IPM indicators. The research show 4 clusters that describe the condition of the Indonesian region and based on the results of cluster validation shows that there are differences in the ordinary Fuzzy C-Means mean algorithm and Fuzzy C-Means using particle swarm optimization.