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Journal : ARRUS Journal of Engineering and Technology

Application of Ensemble K-Modes and SWFM for Grouping Sulawesi Tengah Regions by Underdeveloped Indicators Rais, Zulkifli; Aidid, Muhammad Kasim; Amira, Husnul
ARRUS Journal of Engineering and Technology Vol. 5 No. 1 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/jetech4014

Abstract

This research aims to determine the best final clustering results and clustering statistics for regencies/cities in Central Sulawesi based on underdeveloped region indicators. The study uses categorical and numerical data variables, consisting of 10 numerical variables and 3 categorical variables. The methods used in this research are the mixed data Ensemble K-Modes and the Similarity Weight and Filter Method (SWFM). The best mixed data clustering method shows that the Ensemble K-Modes method produces better clustering results than the SWFM method, as Ensemble K-Modes has a higher accuracy score of 0,8462