Treffer: Penerapan K-Means Clustering Untuk Segmentasi Penjualan Di Minimarket Mardi Dengan Pendakatan Machine Learning.

Increasing the effectiveness of marketing strategies is an urgent need in the current competitive era. This research aims to help Minimarkt Mardi understand customer purchasing patterns through the application of the K-Means algorithm for sales segmentation. With this method, transaction and sales data are processed to produce customer clusters based on purchasing behavior patterns. Clustering was carried out using Anaconda software with the Python programming language, utilizing libraries such as Pandas, NumPy, and Scikit-learn. Evaluation of cluster quality is carried out using the Davies-Boulding Index (DBI). The research results show the division of customers into 3 main clusters, including low, medium and high categories. These findings offer opportunities for Mardi Minimarket to improve business performance significantly. [ABSTRACT FROM AUTHOR]

Peningkatan efektivitas strategi pemasaran menjadi kebutuhan mendesaak di era kompetitif seperti sekarang. Penelitian ini bertujuan untuk membntu Minimarkt Mardi dalam memahami pola pembelian pelanggan melalui penerapan algoritma K-Means untuk segmentasi penjualan. Dengan metode ini, data tranksaksi dan penjualan diolah untuk menghasilkan klaster pelanggan berdasarkan pola perilaku pembelian. Klasterisasi dilakukan menngunakan perangkat lunak anaconda dengan bahasa pemrograman Pyhton, memanfaatkan putaka seperti Pandas, NumPy, dan Scikit-learn. Evaluasi kualitas klaster dilakukan dengan Davies-Boulding Index (DBI). Hasil penelitian menunjukkan pembagian pelanggan ke dalam 3 klaster utama, mencakup kategori rendah, sedang, dan tinggi. Temuan ini menawarkan peluang bagi Minimarket Mardi untuk meningkatkan kinerja bisnis secara signifikan. [ABSTRACT FROM AUTHOR]

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