Clustering MSMEs in Jambi Province Using K-Means Algorithm for Policy Strengthening

Hetty Rohayani; Noneng Marthiawati; Saleh Yaakub

doi:10.35877/454RI.jinav4844

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JINAV: Journal of Information and Visualization

Vol. 7 No. 1 (2026), Pages 83-96 · 2026-04-30

OriginalPaper | Open access | Published: April 30, 2026

Clustering MSMEs in Jambi Province Using K-Means Algorithm for Policy Strengthening

Hetty Rohayani, Noneng Marthiawati, Saleh Yaakub

JINAV: Journal of Information and Visualization, Vol. 7 No. 1 (2026), pp. 83-96 https://doi.org/10.35877/454RI.jinav4844 Published: 2026-04-30

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Abstract

Micro, Small, and Medium Enterprises (MSMEs) play an important role in supporting economic growth in Jambi Province. However, the distribution of MSMEs across regencies and cities has different characteristics, requiring further analysis to identify distribution patterns. This study aims to cluster MSME distribution in Jambi Province using the K-Means algorithm as an unsupervised machine learning approach. The study used MSME data from 2019–2023 obtained from the Regional Office of Cooperatives and Small Enterprises of Jambi. Data processing was conducted using Python through preprocessing, the Elbow Method, K-Means clustering, and cluster evaluation using the Silhouette Coefficient and Davies-Bouldin Index (DBI). The results showed that the optimal number of clusters was three: Low Cluster (C0), Medium Cluster (C1), and High Cluster (C2). The Low Cluster included Merangin, Sarolangun, and Tebo Regencies, while the High Cluster included Batanghari, Kerinci, Muaro Jambi Regencies, and Jambi City. The evaluation results produced a Silhouette Coefficient value of 0.81 and a DBI value of 0.21, indicating that the clustering model has good quality and optimal cluster separation. This study can support regional development planning and targeted MSME policy formulation in Jambi Province.

Keywords

MSMEs Jambi Province K-Means Algorithm Clustering Policy Strengthening

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How to Cite

Rohayani, H., Marthiawati, N., & Yaakub, S. (2026). Clustering MSMEs in Jambi Province Using K-Means Algorithm for Policy Strengthening. JINAV: Journal of Information and Visualization, 7(1), 83–96. https://doi.org/10.35877/454RI.jinav4844