Implementation of Apriori Algorithm for Sales Data Analysis (Case Study: Toko Ud. Suryani)

Abstract

Transaction data owned by a store or supermarket every day is sure to increase, but it is often found that the transaction data is just stored and notused. This is what happened at the UD. Suryani store, where the existing transaction data has not been used properly, even though the collection of transaction data has the potential for information that can be processed to produce useful new knowledge. This transaction data processing can be done with data mining techniques. One of the data-mining techniques that can be used is the association rule method. One of the data retrievalalgorithms with association rules is the Apriori algorithm. This algorithm serves to determine the association relationship of a combination of itemsand is suitable to be applied when there are several item relationships to be analyzed. The purpose of this research is to apply data mining to the transaction data for the last one year in the UD. Suryani store. The data mining processing process is carried out with the rapidminer application and from nine trials with different combinations of minimum support and minimum confidence values for 13,490 transaction data, the results obtained are that the item most purchased by consumers is the Masako Sapi Renteng 10g with a support value of 14,5% and for items that are often purchasedtogether, if you buy Eggs and Blue Band 200g, you will buy Kompas Kemasan 1kg, with the highest confidence value of 66.5%