Implementation of the Association Method in the Analysis of Sales Data from Manufacturing Companies

Abstract

The company produces sales data every day. Over time, the data increases, and the amount becomes very large. The data is only stored without understanding the benefits that exist from these data due to limitations in proper knowledge in analyzing the data, especially transaction data. Sale. To overcome these problems, a study focused on reprocessing sales transaction data in 2018 with a data mining technique approach using the Knowledge Discovery in Database (KDD) concept using the association method and apriori algorithm and a supporting application, namely RapidMiner. This study aims to help companies find customer buying habits or patterns based on 2018 sales transaction data. The results of this study produce 316 association rules where the best rules are generated on record 309 with PRO 889 & PRO 868 PRO 869 rules.