Implementasi Algoritma K-Means Dalam Pengelompokan Data Penjualan CV. Widuri Menggunakan Orange

Abstract

Sales is one of the company's activities to get profit or what is commonly called profit. To achieve the desired profit, companies make every effort to produce the best products for their consumers to enjoy. As is the case with CV Widuri, one of the companies engaged in making snacks or snacks such as pilus, macaroni, uril macaroni, basreng, round tofu, and seblak. Sales data can be utilized by grouping products that are easy to sell and difficult to sell, so that companies can minimize the increase in the number of leftover goods (BS). By using clustering techniques in data mining, companies can identify potential products by grouping the products produced. Basically, the K-Means clustering algorithm can be applied to the problem of understanding consumer behavior to identify opportunities to bring new products to market. K-Means algorithm can also be used to collect objects from many objects to make it easier to describe the properties and characteristics of each group. From the data obtained from calculations using the orange application, namely cluster 1 (C1) 104 transactions, cluster 2 (C2) 1 transaction, cluster 3 (C3) 139 transactions, cluster 4 (C4) 95 transactions, cluster 5 (C5) 102 transactions, cluster 6 (C6) 76 transactions, and cluster 7 (C7) 97 transactions. With the provisions of products that are easy to sell, namely pilus and products that are difficult to sell, namely pilus bantat.
Keywords; Clustering, Data Mining, K-Means, Orange, Sales.