Segmentasi Pembelian Produk Menggunakan Algoritma K-Means Berdasarkan Clusterisasi pada pemilihan menu yang ada diUMKM Kuliner - Annisa, Lolanda Hamim; Rusvinasari, Dian (Jurnal Informatika: Jurnal Pengembangan IT, 2024)
Marketing strategy can be seen as one of the bases used in preparing comprehensive SME planning. One of the SMEs that will be highlighted in this research is restaurants. Customer loyalty is an important thing that must be maintained by companies for the sustainability of the company and can improve good relationships between service provider companies and their customers. K-Means Cluster Analysis is a non-hierarchical cluster analysis method that attempts to partition existing objects into one or more clusters or groups of objects based on their characteristics, so that objects that have the same characteristics are grouped in the same cluster and objects that have similar characteristics. different groups are grouped into other clusters. The purpose of this research is to find out how to group menus that have high selling power and also the relationship between one menu variable and another menu when a transaction or purchase occurs by a customer. The results obtained in this research were to create a segmentation of products purchased by customers in the period May-November 2023 in SMEs operating in the culinary sector in the Central Java area. The results showed that the types of products most frequently purchased were Chicken Rice, Tea, Chicken, White Rice which is at the highest purchase order. Where Chicken Rice was purchased 5409 times, Tea 1867 times, White Rice 1452 times, Chicken 1110 times. In the K-Means Algorithm to determine which products sell frequently and require more inventory and which do not .