Penerapan Data Mining Menggunakan Metode K-Means Clustering Untuk Analisa Penjualan Toko Myam Hijab Penajam - Gita Aprilianur; Elvin Leander Hadisaputro (Teknik Komputer Politeknik Negeri Sriwijaya, 2022)
Myam Hijab shop is a store that specializes in selling hijab, but of the various hijabs that are sold, of course, not all of them sell, some do not. Sales data, purchases of goods and unexpected expenses in Myam Hijab are not well structured, so the data only serves as a store archive and cannot be used to develop marketing strategies. Therefore, it is necessary to apply data mining using the K-Means method. at the Myam Hijab shop. The K-Means method can be applied to the Myam Hijab Store to find out which hijab sales are selling, selling and not selling. The application of the K-Means method at this Myam shop is by grouping hijab stock data. Then select 3 random groups as the initial centroid. After the data for each group did not change, it was seen that in the end there were 24 products that were selling well, 59 products that were selling well, and 17 products that were not selling well. Then, the application of the K-Means method on Rapidminer is done by entering product stock data, namely initial stock, sold stock and ending stock, which will be converted into a database in Ms.Excel, the data will be connected to Rapidminer Tools and processed. and form K-means. After that, Rapidminer will produce which products are in high demand, high demand, and low demand.