Analisis Data Penjualan Menggunakan Algoritma K-Means Clustering Pada Toko Superindo

Authors

  • Kelvin Hidayat Institut Informatika dan Bisnis Darmajaya
  • Muhammad Rezky Adytama Institut Informatika dan Bisnis Darmajaya
  • Hapip Aditya Darmawan Institut Informatika dan Bisnis Darmajaya
  • Yanda Arnando Institut Informatika dan Bisnis Darmajaya
  • Abdul Mukarim Institut Informatika dan Bisnis Darmajaya

Keywords:

Data mining, Algoritma K-means, Clustering, Analisis Penjualan.

Abstract

Supermarket are increasingly popular among consumers for transactions, with superindo being one of the leading ones behaviour and optimize sales through sales data analysis. Data mining, especially the k-means clustering method, is used to group sales data based on certain characteristics, so taht it can halp in formulating more targeted marketing strategies. This research uses sales data from superindo for april 2024 and is analyzed using the clustering method with the k-means algorithm. The research results show that applying this method is effective in grouping sales data into several clusters, which provides valuable insight clustering results which can be used to improve superindo’s marketing strategy. This research provides a strong basis for the development of more effective marketing strategies.

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Published

2025-04-21

How to Cite

Kelvin Hidayat, Muhammad Rezky Adytama, Hapip Aditya Darmawan, Yanda Arnando, & Abdul Mukarim. (2025). Analisis Data Penjualan Menggunakan Algoritma K-Means Clustering Pada Toko Superindo. JoDMApps (Journal of Data Science Methods and Applications), 1(1), 1–6. Retrieved from https://journal.darmajaya.ac.id/index.php/JoDMApps/article/view/904

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