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IMPLEMENTATION AND COMPARISON ANALYSIS OF APRIORI AND FP-GROWTH ALGORITHM PERFORMANCE TO DETERMINE MARKET BASKET ANALYSIS IN BREILIANT SHOP
Acep Ahman Hidayat, Ali Rahman, Resi Mustifa Wangi, Rahmat Zaenal, Rifqi Syamsul Fuadi

Department of informatics, UIN Sunan Gunung Djati
Bandung, Indonesia


Abstract

The creativity of an online store owner who develops a business in a retail business in determining a marketing strategy will affect his competitive ability with other online stores. However, services that are in accordance with costumers attitude is a stuff that should be awared by shop owners in order to improve not only customer satisfaction but also store income.The method used in this study is Market Basket Analysis to know customers attitude by analyzing data from sales transactions to show customers attitude toward one sold item and the others. Research aimed that it is necessary to have a system that can help to form a combination among products using the association rule method, the algorithm used to analyze this method is apriori and fp-growth algorithm. Result from data analysis test using monthly sales transaction data of cosmetics in Breiliant Store during November 2018 . It could be concluded that a combination of products which have strong support and confidence were Original Liquid Bleaching Seeds, Harva Peeling Gel and Castor oil. It had support value of 8.8% and 30% confidence value, with a filtering time of 0.036 seconds.

Keywords: data mining, Association Rule, Apriori algorithm, FP-Growth algorithm.

Topic: Computer Science

Link: https://ifory.id/abstract/DJwLyZaeAP9c

Conference: The 4th Annual Applied Science and Engineering Conference (AASEC 2019)

Plain Format | Corresponding Author (Acep Ahman Hidayat)

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