IMPLEMENTATION OF THE K-NEAREST NEIGHBOR METHOD FOR SALES PREDICTION OF BEST-SELLING HOUSEHOLD PRODUCTS

Abstract

Household products in the Idola 2 Store certainly have a large number, making it difficult for the store to determine which products have the best selling sales. This research aims to determine the best-selling household products that are most likely to sell at Idola 2 Stores using the K-Nearest Neighbor (K-NN) method and to apply the K-Nearest Neighbor (K-NN) method to predict best-selling products by utilizing sales data. This research uses the RAD (Rapid Application Development) system development method which consists of several stages. The results of this study have created a system using the K-NN method in predicting the determination of best-selling household products. Based on the results of the K-NN method process in predicting the best-selling household products, it is obtained from 20 products, there are 5 products that are included in the best-selling household products, namely Motif Glass Jars, Plastic Jars, Foot Mats, Hanger and Multipurpose Shelves. From this data, the Idol 2 Store can predict what products are likely to have good sales or sell well in the next month.