File Download

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher


Kim, Yunho
Mathematical Imaging Analysis Lab.
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Revisiting fuel subsidies in Indonesia using k-means, PAM, and CLARA

Prasetyo, Fajar AgungCaraka, Rezzy EkoKim, YunhoGoldameir, Noor EllSulistyowatiTyasti, Avia EnggarUgiana, Prana Gio,Anggoro, FaisalRamadhani, MPardamean, B
Issued Date
IAENG International Journal of Computer Science, v.50, no.3, pp.858 - 865
Indonesia is one of the countries in the world that still applies subsidies for fuel oil. By the law, the Indonesian government must ensure the supply and distribution of fuel for all Indonesian people. To implement this policy properly, understanding the pattern of fuel consumption is fundamental. In this study, clustering will be used to determine the categories of districts and cities based on subsidized fuel consumption patterns. Our research used several methods to compare which cluster method is the most optimal; the methods include k-means, Partitioning Around Medoids (PAM), and Clustering Large Applications (CLARA). The results show that k-means is the best clustering method with the highest Dunn index and Silhouette coefficient compared to others. The optimum cluster number we get is two and represents fuel consumption from several districts and cities. Some districts and cities had under-average consumption and needed to be monitored
International Association of Engineers
Keyword (Author)
CLARAfuel subsidiesk-meansPAM


Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.