Implementasi Data Mining Penjualan Produk Pakaian Dengan Algoritma Apriori

Abstract

The problem faced by the Tanjung Redjo clothing store is the lack of management of sales data and irregular arrangement of clothing products. The arrangement of the location of clothing products on the shelf is not well regulated. The speed of service to customers can be improved by making the layout of clothing products good and orderly, so that store staff can find clothing products quickly. Shoppers can also search and view apparel accessories that are often sold together quickly, potentially increasing store sales turnover. A better and more organized arrangement of clothing products can be done by analyzing sales transactions that occur daily at the store by using the Apriori algorithm. By using this algorithm, the shop owner can find out the tendency of a combination of clothing products that are often sold at the same time, so that the shop owner can arrange the layout of clothing products well and regularly so that buyers or employees can find and retrieve clothing products quickly. How the Apriori algorithm works to find a combination of clothing products that are often sold simultaneously from a sales transaction. Rules applied If buying KA-701 and KK-201 and SP-2001, then buy ST-651. Support and Confidence values are calculated until 4 combination items are obtained to get the best selling associative rule output output.