Application of Apriori Algorithms to Determine Associations in Outdoor Sports Equipment Stores
Abstract
A good sales strategy has an effect on increasing the number of sales of goods. Problems that often occur in outdoor sports equipment stores are the difficulty in determining sales strategies because there is not much interest in outdoor sports in the community. In addition, the amount of inventory in the store is excessive, which affects the sales cycle of goods. One way to help determine strategy is to use apriori algorithm. In this method can determine consumer shopping behavior patterns. Apriori algorithms are part of the data mining analysis association. This algorithm is used to determine association rules. In the study, a combination of sports equipment purchased by consumers will be determined. Determination of the combination starts from 1 itemset to 3 itemsets, the combination of rule association produces different sales transaction patterns. The results of the study in the form of a combination of consumer shopping behavior patterns that will be used as recommendations for shop owners in determining the sales strategy. The resulting Rule association will help sales promotions and add the amount of inventory that many customers buy.