Sistem Penunjang Keputusan Pemasaran Produk X Menggunakan Metode K-Means - Ach. Syuhbanul Yaumi; Zainul Zulfiqkar; Aryo Nugroho (Systemic: Information System and Informatics Journal, 2020)
The problem that is currently in store is the difficulty to find out which product x is currently in high demand or is most widely used by consumers so that inventory of product x can be met according to customer demand and does not occur out of stock. Therefore, in the research grouping with the K-Means method for marketing product x is one way to determine customer choices for product x consumed. In this study grouping data from questionnaires or questionnaires that are distributed in stores, then the data are grouped into 2 groups using one of the clustering algorithms, K-Means. The data used are data collected by 366 respondents of store customers. After the data is processed using one of the data mining methods, the K-Means algorithm, shows that cluster 1 is a type A consumer group with a percentage of 33%, while cluster 2 is a type B consumer group with a percentage of 67%.