research-article

Real Market Basket Analysis using Apriori and Frequent Pattern Tree Algorithm

Authors:

Michael Albert Christian,

Nathanael Nathanael,

Annisa Mauliani,

Ariani Indrawati,

Lindung Parningotan Manik,

Zaenal AkbarAuthors Info & Claims

IC3INA '21: Proceedings of the 2021 International Conference on Computer, Control, Informatics and Its Applications

Pages 161 - 165

https://doi.org/10.1145/3489088.3489133

Published: 13 February 2022 Publication History

Abstract

Recently, data mining has been implemented in various fields, including business and telecommunications. Data mining is a technique for extracting and detecting patterns in massive data sets that combines machine learning, statistics, and database systems. One of the most important use-cases in data mining is finding the high-frequency patterns between the set of itemset called association rules. Association rule mining is a well-researched technique for finding some relations between variables in large databases. This paper aims to measure the performance of the Apriori and Frequent Pattern Tree algorithms by comparing them using several points of comparison. Then we compared the outputs, whether they produce the same or different rules, to find out whether the way the two algorithms work is similar or not. After that, we looked for the itemsets that best match the reality in the market by giving them to a user who had transaction data from his spare parts shop.

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Cited By

Sajwan ITripathi R(2024)Unveiling Consumer Behavior Patterns: A Comprehensive Market Basket Analysis for Strategic Insights2024 Sixth International Conference on Computational Intelligence and Communication Technologies (CCICT)10.1109/CCICT62777.2024.00067(372-377)Online publication date: 19-Apr-2024
https://doi.org/10.1109/CCICT62777.2024.00067
Ishfaq UAli TDaud AAlreshoodi MIrshad A(2024)Modeling Topic-Specific Influential Users in QA Forums Using Association Rule MiningIEEE Access10.1109/ACCESS.2024.351770212(196498-196516)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3517702

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Real Market Basket Analysis using Apriori and Frequent Pattern Tree Algorithm

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cover image ACM Other conferences

IC3INA '21: Proceedings of the 2021 International Conference on Computer, Control, Informatics and Its Applications

October 2021

204 pages

ISBN:9781450385244

DOI:10.1145/3489088

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 13 February 2022

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IC3INA 2021

IC3INA 2021: The 2021 International Conference on Computer, Control, Informatics and Its Applications

October 5 - 6, 2021

Virtual/online conference, Indonesia

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Cited By

Sajwan ITripathi R(2024)Unveiling Consumer Behavior Patterns: A Comprehensive Market Basket Analysis for Strategic Insights2024 Sixth International Conference on Computational Intelligence and Communication Technologies (CCICT)10.1109/CCICT62777.2024.00067(372-377)Online publication date: 19-Apr-2024
https://doi.org/10.1109/CCICT62777.2024.00067
Ishfaq UAli TDaud AAlreshoodi MIrshad A(2024)Modeling Topic-Specific Influential Users in QA Forums Using Association Rule MiningIEEE Access10.1109/ACCESS.2024.351770212(196498-196516)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3517702

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