Application of Apriori Algorithm Method in Sales Analysis of Mountain Bag Brands in Post Stores 1

Abstract

Nowadays, climbing mountains has become a lifestyle for young people. Outdoor industries that produce clothing, bags and sports shoes participate in developing and following the desires of the market. Each company in producing its products has a special brand. Shop Pos 1 is one of the shops that sell various climbing equipment commonly used by climbers to climb mountains. In addition, Pos 1 stores also find it difficult to get updated information about the level of sales per period. Therefore, we need a decision support systems and methods that can be used to determine business strategies that can provide efficient and effective information, namely data mining using a priori technology association methods. The author chooses mountain bag products only as research material by selecting brands, completing Avtech, Consina, Co-tracks, Cozmed, Eiger, Forester, Rei, Loss. In analyzing the data, the writer uses a priori algorithm calculation by testing the hypothesis of two variables between the value of support and the value of trust. After that, a priori algorithm is calculated using Tanagra. Based on analysis conducted by the author, the operator most preferred by climbers is Avtech, Consina, Cozmed. From these results, it can be used by Pos 1 to prepare brand inventory of mountain bag products that are widely bought by buyers and increase brand inventory. Keywords: Bag Brand, Data Mining, apriori algorithm.