ARRUS Journal of Engineering and Technology
Vol. 5 No. 1 (2025)

Application of Ensemble K-Modes and SWFM for Grouping Sulawesi Tengah Regions by Underdeveloped Indicators

Rais, Zulkifli (Unknown)
Aidid, Muhammad Kasim (Unknown)
Amira, Husnul (Unknown)

Article Info

Publish Date
10 Jun 2025

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

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Journal Info
ARRUS Journal of Engineering and Technology
Website

Abbrev

jetech

Publisher

Yayasan Ahmar Cendekia Indonesia

Subject

Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science

Description

ARRUS Journal of Engineering and Technology preserves prompt publication of manuscripts that meet the broad-spectrum criteria of scientific excellence. Areas of interest include, but are not limited to: Aerospace Engineering Architecture Evaluations Automation and Mechatronics Engineering ...