Grouping Building Material Sales for Management Optimization with the K-Means Algorithm

Sales transactions at the Pedi Building Store are recorded in daily logbook provided by store, so that it cannot be immediately known which types of products selling well or not well. To overcome this problem, an analysis sales data is carried out using K-Means Algorithm. The algorithm requires as many input parameters and divides a set objects into clusters level similarity between members one cluster high, while with other very low. This study aims to determine sell don't used 100 samples 2 formed, namely unsold goods (Cluster 1) salable 2). With Algorithm, produces 4 items 1), 96 results application was developed for managed makes easy sellers manage form processes less