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All Journal Internet of Things and Artificial Intelligence Journal
Lestari, Silvia Windri
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Association Analysis in Java Ateka for Stationery Sales Promotion Using the FP-Growth Algorithm Wardani, Syafa Wajahtu; Lestari, Silvia Windri; Daffa, Nauffal Ammar; Tahyudin, Imam
Internet of Things and Artificial Intelligence Journal Vol. 2 No. 3 (2022): Vol. 2 No. 3 (2022): Volume 2 Issue 3, 2022 [August]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (688.874 KB) | DOI: 10.31763/iota.v2i3.569

Abstract

Every company or organization must have the right strategy to continue business or organizational activities. If not used, product sales data at the company will only become a pile of data; of course, it is regrettable if it is not used properly. The company can use the most product sales data to determine the next marketing strategy. To find out this data (the most sales), Association Rules Analysis is needed on the FP-Growth Algorithm method. This research aims to determine the association rule of Java ATK sales using the FP-Growth algorithm. This algorithm can be used for extensive data sets and to process Big Data. The results of this study are the FP Growth algorithm using association rules, which can be implemented in bookstore sales data with support count and minimum confidence parameters. A decimal value of 0.8 can form a product purchase correlation to increase stationery sales in Java Ateka. The rule obtained from the results of the FP-Growth calculation is that there are three transactions where if you buy item A, you will buy item B.
Co-Authors Daffa, Nauffal Ammar Imam Tahyudin Wardani, Syafa Wajahtu