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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi
Putu Christian Juan Yakhin Ofel Mone
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Computer Science & IT Economics, Econometrics & Finance

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Penerapan Algoritma K-Means Clustering untuk Mengelompokkan Pola Bermain Pemain TheoTown Putu Christian Juan Yakhin Ofel Mone; Ni Gusti Ayu Putu Harry Saptarini; Gde Brahupadhya Subiksa
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 2 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No2.pp513-523

Abstract

City-building simulation games like TheoTown trigger diverse player behaviors, yet the segmentation between strategic and satirical players remains unmapped. This study classifies TheoTown player patterns using the Knowledge Discovery in Databases (KDD) framework and k-means clustering on 1,084 respondents. Data were preprocessed with one-hot encoding and min-max scaling to eliminate Euclidean distance bias. Multi-criteria validation, specifically the Silhouette Coefficient, indicated the most rational separation at K=2 (score 0.1758). The novelty of this study lies in the mixed-method approach integrating K-Means with multi-criteria validation and qualitative content analysis in a sandbox ecosystem. Quantitative results were validated qualitatively via word clouds from respondents' essays. Findings reveal two main archetypes: Cluster 0 (Strategic & Welfare Builders, 57.29%), focusing on economic and spatial efficiency, and Cluster 1 (Experimental & Satirical Players, 42.71%), utilizing the game for radical experiments and government critique. This study indicates that simulation games can serve as a medium for players' psychographic expression.
Co-Authors Gde Brahupadhya Subiksa Ni Gusti Ayu Putu Harry Saptarini