PENERAPAN METODE K-MEANS CLUSTERING UNTUK ANALISA BARANG TERLARIS DI DEPO BANGUNAN JAKARTA

Authors

  • Baginda Oloan Lubis Universitas Bina Sarana Informatika
  • Agus Salim Universitas Bina Sarana Informatika
  • Firstianty Wahyuhening Fibriany Universitas Bina Sarana Informatika
  • Juniato Sidauruk Universitas Bina Sarana Informatika
  • Suharjanti Suharjanti Universitas Bina Sarana Informatika

DOI:

https://doi.org/10.31849/62xjmm66

Keywords:

K-Means Clustering, Data Mining, Building Depot

Abstract

Information systems are developing rapidly due to the increasing need for information, which also results in the growth of large amounts of data. However, it is important that this data can be processed into quality information that is useful to users. Depo Bangunan Jakarta, which specializes in selling various types of hand, power, machine, and accessory tools, faces this challenge. With various types and sizes of goods, Depo Bangunan Jakarta must manage its stock well to avoid wastage in procurement. Data mining is a solution for business people to increase their company's sales. The method used in data mining includes K-Means Clustering, which classifies data into several groups based on their similar characteristics. With this clustering, it is expected that businesses can identify the right marketing strategy for their consumers. The results showed that items such as 4" WA60 LIPPRO Flexible Grinding Stone, PH2 X 65mm BOSCH Screw Eye (++), FERRARI KW 1 Iron Chalk, and 3mm Sling Clamps are the best-selling items in Jakarta Building Depot.

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Published

2025-05-26

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Vol. 7 No. 2 (2025): Publikasi artikel ZONAsi: Jurnal Sistem Informasi Periode Mei 2025

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How to Cite

[1]
“PENERAPAN METODE K-MEANS CLUSTERING UNTUK ANALISA BARANG TERLARIS DI DEPO BANGUNAN JAKARTA”, zn, vol. 7, no. 2, pp. 624–638, May 2025, doi: 10.31849/62xjmm66.