Product Layout Analysis Based on Consumer Purchasing Patterns Using Apriori Algorithm

Made Leo Radhitya; Ni Komang Mira  Widiantari; Made Dwi Putra  Asana; Bagus Kusuma Wijaya; I Gede Iwan Sudipa

doi:10.47709/cnahpc.v6i3.4400

Authors

Made Leo Radhitya Institut Bisnis dan Teknologi Indonesia, Denpasar, Indonesia
Ni Komang Mira Widiantari Institut Bisnis dan Teknologi Indonesia, Denpasar, Indonesia
Made Dwi Putra Asana Institut Bisnis dan Teknologi Indonesia, Denpasar, Indonesia
Bagus Kusuma Wijaya Institut Bisnis dan Teknologi Indonesia, Denpasar, Indonesia
I Gede Iwan Sudipa Institut Bisnis dan Teknologi Indonesia, Denpasar, Indonesia

DOI:

10.47709/cnahpc.v6i3.4400

Keywords:

Apriori algorithm, Data mining, Association analysis, High utility itemset mining

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Abstract

In every self-service store, it is certain to have a sales transaction data, where the data will continue to grow every day. But in self-service stores the data is only a record of sales at the store. Whereas transaction data can be used as information on how consumer purchasing patterns when shopping at the store, but not all supermarkets know this. So this research aims to find information on these purchasing patterns, where to do this research using the apriori algorithm which is part of the association technique which is also part of data mining, where in its application it will calculate the support value, confindence value and will be tested using the lift ratio. And after the calculation is carried out, optimization will be carried out using the high utility itemset mining variable which will calculate the highest profit value on the product, so that based on the calculation, the final result is obtained with a support value of 85%, a confidence value of 86%, a lift ratio test of 1.01 and the high utility gets the highest result of Rp. 567,000.

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