What type of study is this?

This is a Quantitative Study study.

Analisis Klasterisasi Data pada Berbagai Bidang Menggunakan Algoritma K-Means: Studi Kasus dalam Kriminalitas, Ekonomi, Politik, Administrasi Digital, dan Perdagangan

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Analysis shows K-Means effectively clusters diverse data domains like crime and economics, suggesting significant insights for decision-making.

K-Means successfully clusters data, revealing hidden patterns that aid decision-making across multiple domains.
Analysis utilized datasets from fields like crime, digital administration, and international trade to demonstrate versatility.
Evaluation metrics included the Silhouette Score and Davies-Bouldin Index, confirming cluster quality in diverse data contexts.
Findings highlight the adaptability of K-Means and potential for advanced clustering methods in multidomain analysis.

Pratama et al. (2025) studied this question.

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View Full Paper

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Authors

Analysis shows K-Means effectively clusters diverse data domains like crime and economics, suggesting significant insights for decision-making.

K-Means successfully clusters data, revealing hidden patterns that aid decision-making across multiple domains.
Analysis utilized datasets from fields like crime, digital administration, and international trade to demonstrate versatility.
Evaluation metrics included the Silhouette Score and Davies-Bouldin Index, confirming cluster quality in diverse data contexts.
Findings highlight the adaptability of K-Means and potential for advanced clustering methods in multidomain analysis.

Pratama et al. (2025) studied this question.

View Full Paper

Ask AI

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