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.

Downloads

Download data is not yet available.

Author Biographies

I KADEK SONA DWIGUNA, Universitas Udayana

Program Studi Matematika, Fakultas MIPA, Universitas Udayana

G.K. GANDHIADI, Universitas Udayana

Program Studi Matematika, Fakultas MIPA, Universitas Udayana

LUH PUTU IDA HARINI, Universitas Udayana

Program Studi Matematika, Fakultas MIPA, Universitas Udayana

Published
2022-08-31
How to Cite
DWIGUNA, I KADEK SONA; GANDHIADI, G.K.; HARINI, LUH PUTU IDA. IMPLEMENTASI FUZZY C-MEAN DAN ALGORITMA PARTICLE SWARM OPTIMIZATION UNTUK CLUSTERING KABUPATEN/KOTA DI INDONESIA BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA. E-Jurnal Matematika, [S.l.], v. 11, n. 3, p. 191-198, aug. 2022. ISSN 2303-1751. Available at: <https://ojs.unud.ac.id/index.php/mtk/article/view/90745>. Date accessed: 22 nov. 2024. doi: https://doi.org/10.24843/MTK.2022.v11.i03.p380.
Section
Articles

Most read articles by the same author(s)

1 2 3 > >>