Mapping the Distribution of Pak Iwan’s Tofu Sales Area Using the K-Means Method Based on Sales Volume

Authors

  • Dimas Arya Bintara Universitas Royal
  • Muhammad Amin Universitas Royal
  • Ahmad Muhazir Universitas Royal

DOI:

https://doi.org/10.35870/ijmsit.v6i2.8802

Keywords:

K-Means Clustering, Data Mining, Distribution Area Mapping, Product Sales Level

Abstract

The rapid development of information technology has reshaped many sectors, particularly business activities. In this study, raw sales data are processed into useful information through the grouping of distribution areas based on product sales levels. A quantitative approach is applied by using historical distribution and sales data as the basis of analysis. The findings show that K-Means can organize multidimensional data in a systematic and objective manner, producing regional classifications that are more reliable than decisions based only on intuition or prior experience. The clustering results classify seven marketing areas into three groups. Cluster 1, categorized as Very Popular, includes Air Joman and Silau Laut. Cluster 2, categorized as Popular, consists of Sidokeno. Cluster 3, categorized as Less Popular, includes Sei Kamah, Pulo Bandring, East Kisaran, and West Kisaran.

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Author Biographies

  • Dimas Arya Bintara, Universitas Royal

    Information Systems Study Program, Faculty of Computer Science, Universitas Royal, Asahan Regency, North Sumatra Province, Indonesia

  • Muhammad Amin, Universitas Royal

    Information Systems Study Program, Faculty of Computer Science, Universitas Royal, Asahan Regency, North Sumatra Province, Indonesia

  • Ahmad Muhazir, Universitas Royal

    Information Systems Study Program, Faculty of Computer Science, Universitas Royal, Asahan Regency, North Sumatra Province, Indonesia

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Published

2026-10-16

How to Cite

Bintara, D. A., Amin, M., & Muhazir, A. (2026). Mapping the Distribution of Pak Iwan’s Tofu Sales Area Using the K-Means Method Based on Sales Volume. International Journal of Management Science and Information Technology, 6(2), 2853-2864. https://doi.org/10.35870/ijmsit.v6i2.8802