K-Means Cluster Analysis for Grouping Small and Medium Enterprises (SMEs) in Pesisir Selatan Regency

Small and Medium Industries (SMEs) play an important role in national economic growth through job creation, improving regional economies, and triggering entrepreneurial spirit. Although most SMEs operate on a limited scale with simple technology, this sector has great potential to grow if it receives sustainable support. However, SMEs in Pesisir Selatan Regency face various challenges, such as limited human resources, difficulty in accessing capital, and low utilization of technology. This study aims to analyze the grouping of SMEs in Pesisir Selatan Regency using the clustering method. Using secondary data on six types of SMEs in 15 sub-districts in 2023, this study applies the K-Means algorithm to group SMEs based on the characteristics of the dominant sector. The clustering results produce three main groups: first, sub-districts with high SME activity in the textile and food sectors; second, sub-districts with low SME activity in almost all sectors; and third, sub-districts with balanced SME activity in various sectors, such as apparel, beverages, furniture, and non-metallic minerals. These findings are expected to provide insight for local governments in formulating more targeted policies for the development of SMEs and equitable distribution of economic growth in Pesisir Selatan Regency.

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Publication Details

Journal
UNP Journal of Statistics and Data Science
Published
2025-05-31
DOI
https://doi.org/10.24036/ujsds/vol3-iss2/364
Primary Topic
Customer churn and segmentation
Type
article
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article

K-Means Cluster Analysis for Grouping Small and Medium Enterprises (SMEs) in Pesisir Selatan Regency

Yenni Kurniawati, Nailul Arrahmi, Chairina Wirdiastuti
UNP Journal of Statistics and Data Science
Customer churn and segmentation
article

K-Means Cluster Analysis for Grouping Small and Medium Enterprises (SMEs) in Pesisir Selatan Regency

Yenni Kurniawati, Nailul Arrahmi, Chairina Wirdiastuti
article en

Abstract

Small and Medium Industries (SMEs) play an important role in national economic growth through job creation, improving regional economies, and triggering entrepreneurial spirit. Although most SMEs operate on a limited scale with simple technology, this sector has great potential to grow if it receives sustainable support. However, SMEs in Pesisir Selatan Regency face various challenges, such as limited human resources, difficulty in accessing capital, and low utilization of technology. This study aims to analyze the grouping of SMEs in Pesisir Selatan Regency using the clustering method. Using secondary data on six types of SMEs in 15 sub-districts in 2023, this study applies the K-Means algorithm to group SMEs based on the characteristics of the dominant sector. The clustering results produce three main groups: first, sub-districts with high SME activity in the textile and food sectors; second, sub-districts with low SME activity in almost all sectors; and third, sub-districts with balanced SME activity in various sectors, such as apparel, beverages, furniture, and non-metallic minerals. These findings are expected to provide insight for local governments in formulating more targeted policies for the development of SMEs and equitable distribution of economic growth in Pesisir Selatan Regency.

UNP Journal of Statistics and Data ScienceVol. 3(2)
State University of Padang (ID)
Openalex Percentile: Top 85%
Customer churn and segmentation
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K-Means Cluster Analysis for Grouping Small and Medium Enterprises (SMEs) in Pesisir Selatan Regency — Yenni Kurniawati, Nailul Arrahmi, et al. · UNP Journal of Statistics and Data Science (2025) | TGRS Research Map | TGRS