Pengelompokkan Data Pembelian Tinta Dengan Menggunakan Metode K-Means - Susliansyah, Susliansyah; Sumarno, Heny; Priyono, Hendro; Hikmah, Noer (J-SAKTI (Jurnal Sains Komputer dan Informatika), 2019)
PT. Mayer Indah Indonesia is engaged in the production of goods, where the most important part to prepare the needs for production needs is the purchasing department, but in the purchasing section it is difficult to determine which items must be bought a lot, are and few in meeting the demand requirements of each part because of the needs goods for production are very unpredictable, eventually causing some goods demand not to be fulfilled because the goods are out of stock. To solve the problems experienced by the purchasing part, datamining using clustering algorithm is k-means method, where the initial stages determine the centroid randomly and do the first iteration calculation and determine the new centroid from the first iteration, then the second iteration calculation is done, because the results of the first and second iterations in the smallest layout of the three groups, the calculation stops. The results obtained by using the ink purchase data seen from the three attributes of incoming goods, items purchased and stock of goods, making it easier and help the purchasing department in classifying items that must be purchased a lot, medium and little.