E-Commerce Recommender System on the Shopee Platform Using Apriori Algorithm

  • Rachmi Helfianur Telkom University
  • ZK Abdurahman Baizal Computational Science, Faculty of Informatics, Telkom University
https://doi.org/10.34818/INDOJC.2022.7.2.650
Abstract views: 535 , 650 downloads: 958
Keywords: Recomennder System, Apriori Algorithm, E-Commerce, Association Rules

Abstract

The development of E-Commerce continues to increase every year, and all online shopping platforms continue to increase competition. Shopee as an online shopping platform offers various product categories that users need. To make it easier for users when shopping online, it is necessary to implement a product recommender system in E-Commerce. Therefore, in this study, we will build a recommender system using the a priori algorithm. The apriori algorithm is very widely used to find out the buying pattern of each user by looking at a combination of itemset. many recommender systems in e-commerce use various methods used, and provide recommendation results that display popular products, and based on the query results obtained. From the results of previous studies, there are similarities between products that have been liked by customers, so they do not have the best recommendations. Therefore, in this study we apply an apriori algorithm to add user confidence to the given recommendations, and to avoid overspecialization. In this research, we take the domain of electronics goods. In this study, the system produces the best value for association rules with a support value of 0.01, confidence 1.00, and lift 97.35.

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Published
2022-08-01
How to Cite
Helfianur, R., & Baizal, Z. A. (2022). E-Commerce Recommender System on the Shopee Platform Using Apriori Algorithm. Indonesia Journal on Computing (Indo-JC), 7(2), 53-64. https://doi.org/10.34818/INDOJC.2022.7.2.650
Issue
Vol. 7 No. 2 (2022): August, 2022
Section
Computer Science

Copyright (c) 2022 Rachmi Helfianur, ZK Abdurahman Baizal

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