PENERAPAN ALGORITMA ECLAT DAN APRIORI PADA DATA MINING UNTUK MARKET BASET ANALISIS PENJUALAN

aldino aldino

Abstract


Growth of the retail business makes competition in implementing better marketing strategies. This research aims to analyze the shopping basket or market basket analysis in a mini market. Using two algorithms, namely the Eclat algorithm and the Apriori algorithm to analyze sales data, the purpose of this study is to find out the best algorithm in finding association rules or association rules from sales data and provide information regarding what items are the most sold as well as to find out what items. which must be displayed on the sales shelf at the same time. Based on the results of the implementation of thealgorithms Eclat and Apriori concluded that the algorithm Eclat works better thanalgorithm Apriori can be seen from the process of seeking the rule of 212 Mart sales data, Eclat algorithm produces a rule as much as 86 items with a time of 0.01s.


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DOI: https://doi.org/10.33365/jdmsi.v3i2.2207

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Organized by: The S1 Information Systems Study Program, Faculty of Engineering and Computer Science

Published by: Universitas Teknokrat Indonesia

Website: https://ejurnal.teknokrat.ac.id/index.php/JDMSI

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Article Publish in Jurnal Data Mining dan Sistem Informasi are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.