Open AccessApplication of Apriori Algorithm Method in Sales Analysis of Mountain Bag Brands in Post Stores 1
Author(s) -
Agus Salim,
Mochammad Nizar
Publication year - 2020
Publication title -
jite (journal of informatics and telecommunication engineering)
Language(s) - English
Resource type - Journals
eISSN - 2549-6255
pISSN - 2549-6247
DOI - 10.31289/jite.v4i1.2980
Subject(s) - apriori algorithm , a priori and a posteriori , forester , association rule learning , computer science , advertising , marketing , value (mathematics) , business , operations research , data mining , engineering , machine learning , geography , philosophy , epistemology , forestry
Nowadays, climbing mountains has become a lifestyle for young people. Outdoor industries that produceclothing, bags and sports shoes participate in developing and following the desires of the market. Eachcompany in producing its products has a special brand. Shop Pos 1 is one of the shops that sell variousclimbing equipment commonly used by climbers to climb mountains. In addition, Pos 1 stores also find itdifficult 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 efficientand effective information, namely data mining using a priori technology association methods. The authorchooses 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 algorithmcalculation 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, theoperator most preferred by climbers is Avtech, Consina, Cozmed. From these results, it can be used by Pos 1to prepare brand inventory of mountain bag products that are widely bought by buyers and increasebrand inventory.Keywords: Bag Brand, Data Mining, apriori algorithm.