Penerapan Data Mining Terhadap Data Penjualan Prioduk Kopi Menggunakan Algoritma Apriori

Abstract

Currently, the business competition in the culinary field is very tight. Second Home is a culinary business that sells various coffee products that are in demand by the public. The large number of various coffee products causes a lot of sales transaction data to be generated by Second Home. The sales data is not managed properly, causing accumulation and useless data. The level of useless data can be minimized by using a data mining approach. The Data Mining approach aims to provide new information from coffee product sales data. Apriori algorithm is one of the algorithms of data mining that is able to find out association rules based on consumer buying patterns. Based on consumer purchasing patterns for coffee products, the owner of Second Home can provide recommendations or promotions for certain products. The dataset used in this study is 566 sales transaction data from March to May 2021. The application of data mining to sales data with the Apriori Algorithm produces 2 (two) association rules with a support value of 10% and confidence 60%. The results showed that the products purchased simultaneously were Banana fields and Es Kopi Lava Yo Lah with a confidence value of 69.43%.