Using content-based filtering and apriori for recommendation systems in a smart shopping system

Pebrianti, Dwi and Ahmad, Denis and Bayuaji, Luhur and Wijayanti, Linda and Mulyadi, Melisa (2024) Using content-based filtering and apriori for recommendation systems in a smart shopping system. Indonesian Journal of Computing, Engineering and Design, 6 (1). pp. 58-70. ISSN 2656-1972 E-ISSN 2656-8179

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Abstract

This research is motivated by the increasing significance of online shopping platforms and the challenges faced by users in locating products that align with their preferences and requirements, which can significantly influence the sales performance of online retailers. Consequently, the primary objective of this study is to design and implement a recommendation system capable of iden-tifying suitable products and forecasting the purchase frequency for various product combinations, while also integrating this recommendation system with a smart shopping platform. To achieve this objective, the research employs machine learning techniques, specifically content-based filtering and the Apriori algorithm. Con-tent-based filtering is utilized to analyze user preferences and be-havioral patterns related to visited products, while the Apriori al-gorithm is employed to evaluate support and confidence values for item set combinations, thereby generating frequency values for future transactions involving product combinations. Additionally, a smart shopping system is developed and integrated, enhancing the shopping experience through smartphone applications and streamlining the payment process to facilitate seamless product purchases. The research methodology involves data collection pertaining to products and user preferences, followed by several testing involving a sample group of user respondents. The results demonstrate that the developed recommendation system effectively delivers relevant product recommendations based on user preferences, achieving a confidence value up to 98%. Further-more, the smart shopping system proves capable of independently assisting users throughout the transaction process, thereby enhancing overall user experience and convenience.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Apriori, Content based filtering, Machine learning, Online shopping, Smart shopping system
Subjects:	T Technology > T Technology (General) T Technology > T Technology (General) > T10.5 Communication of technical information
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechanical Engineering Kulliyyah of Engineering
Depositing User:	Dr Dwi Pebrianti
Date Deposited:	05 Apr 2024 11:25
Last Modified:	05 Apr 2024 11:25
URI:	http://irep.iium.edu.my/id/eprint/111762

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