Implementation of Apriori Algorithm for Determining Product Purchase Patterns

Nindy Devita Sari, Bambang Soedijono W A, Asro Nasiri

Abstract


In this study, the implementation of Data Mining association method using Apriori algorithm to determine product purchase pattern. Data obtained from the sales transaction data in the Toko Jaya Putra Bumi Agung in the form of a purchase note that will then be implemented using Apriori algorithm. The data mining technique used is the association rule method to know the pattern between items one and other items using support and confidence. In this study of the calculation process with Apriori algorithm obtained minimum value of support 50% and minimum confidence value 70% then resulting tendency of products purchased by consumers ie if buying cooking oil then buy eggs with confidence 75%. If buying Sumendo coffee then buy sugar with confidence 77.8%. This research is expected to be helpful and useful for the owner of Toko Jaya Putra Bumi Agung to predict and analyze the combinations of what kinds of products are often purchased by consumers simultaneously. For further research need to be developed again by combining other data mining algorithms. Preferably the use of datasets that are used will be better to use larger datasets so that they can obtain higher accuracy values.

Keywords


Apriori, Association Rule, Data Mining, Item,

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DOI: http://dx.doi.org/10.30700/jst.v11i1.1033

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