Implementasi K-Means untuk Melakukan Segmnetasi Produk Berdasarkan Data Transaksi Retail

  • Fatia Amalia Maresti Universitas Logistik dan Bisnis Internasional
  • Woro Isti Rahayu Universitas Logistik dan Bisnis Internasional
  • Maria Bernadina Cintany Lustin Universitas Logistik dan Bisnis Internasional
  • Thiodas Heni Pakpahan Universitas Logistik dan Bisnis Internasional
DOI: https://doi.org/10.47080/saintek.v9i1.3856
Keywords: Elbow Method, K-Means, Product Segmentation, Retail Company

Abstract

Retail companies are one form of business that has experienced significant development. Significant development can lead to many business competitors in the same field. Therefore, every company must be able to find strategies to get the attention of the target market. Fast service and good prices are included in the factors that influence customer interest in making transactions in the retail business. This research aims to classify products into several categories. The method used to perform segmentation is the data mining method with the K-Means algorithm and the elbow method to find the optimal number of clusters. The obtained results of many optimal clusters are 3, namely cluster 0, cluster 1, and cluster 2. The variable that has the most influence on cluster characteristics is the price variable, while the variable that has little influence on cluster characteristics is the quantity variable.

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Published
2025-02-24
How to Cite
Maresti, F., Rahayu, W., Lustin, M. B., & Pakpahan, T. (2025). Implementasi K-Means untuk Melakukan Segmnetasi Produk Berdasarkan Data Transaksi Retail. Jurnal Ilmiah Sains Dan Teknologi, 9(1), 20-32. https://doi.org/10.47080/saintek.v9i1.3856
Issue
Vol 9 No 1 (2025): Jurnal Ilmiah Sains dan Teknologi
Section
Articles

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