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

Kelvin Hidayat
Muhammad Rezky Adytama
Hapip Aditya Darmawan
Yanda Arnando
Abdul Mukarim

Journal of Data Science Methods and Applications
Vol. 1 No. 1 (2025)

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.