Penerapan K-Means pada Pengelompokan Penjualan Produk Smartphone - Fatimah Putri Arfani Hasibuan; Sumarno Sumarno; Iin Parlina (SATESI: Jurnal Sains Teknologi dan Sistem Informasi, 2021)
The development of smartphone technology companies that are increasingly rapidly today has more or less led to competition between these companies, thus requiring developers to find strategies or patterns that can increase product sales and marketing, as is the case at PT. Vivo Communication Indonesia Pematangsiantar branch. One of the strategies is to utilize transaction data by grouping them to see which products are more salable in the market and which are not, so that evaluations can be made in planningthe next Vivo product promotion. The clustering method in this study uses the K-Means Clustering method. The K-Means method is a data mining method that is able to group some data into certain parts. In this paper the sales data that has been obtained will be divided into 3 groups, namely low sales, medium sales and high sales. Based on the results of testing using the K-Means method on Vivo smartphone sales data, it was found that the highest sales group had only 1 data, namely Vivo Y12 3+32GB. So it can be concluded that the K-Means method can be applied to group Vivo smartphone sales, because it is in accordance with the actual sales results.