Published: 2023-08-30
E-Commerce Product Recommendation System Using Case-Based Reasoning (CBR) and K-Means Clustering
DOI: 10.35870/ijsecs.v3i2.1527
Legito, Fegie Yoanti Wattimena, Yulianto Umar Rofi'i, Munawir
- Legito: Sekolah Tinggi Teknologi Sinar Husni
- Fegie Yoanti Wattimena: Universitas Ottow Geissler Papua
- Yulianto Umar Rofi'i: Institut Teknologi dan Bisnis Muhammadiyah Bali
- Munawir: Institut Teknologi dan Bisnis Muhammadiyah Bali
Abstract
This research proposes and implements an e-commerce product recommendation system that combines Case-Based Reasoning (CBR) and K-Means Clustering algorithms. The main aim of this research is to provide more personalized and relevant product recommendations to e-commerce users. The CBR approach leverages users' transaction history to provide customized recommendations, whereas K-Means Clustering groups users with similar preferences increase the relevance of recommendations. This study assesses the effectiveness of the system by conducting a comprehensive evaluation by comparing system recommendations with actual user preferences. The results of this study reveal that the combined approach of CBR and K-Means Clustering can improve the performance of e-commerce product recommendations, ensure the accuracy of recommendations, and produce a more satisfying shopping experience for users. Although there are limitations in terms of the dataset used and the choice of algorithm parameters, this research makes an important contribution in developing a more adaptive and personalized recommendation system for e-commerce platforms.
Keywords
Recommendation Systems ; E-Commerce ; Case-Based Reasoning (CBR) ; K-Means Clustering
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Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 3 No. 2 (2023)
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Section: Articles
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Published: August 30, 2023
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License: CC BY 4.0
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Copyright: © 2023 Authors
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DOI: 10.35870/ijsecs.v3i2.1527
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Legito
Informatics Engineering Study Program, Sekolah Tinggi Teknologi Sinar Husni, Deli Serdang Regency, North Sumatra Province, Indonesia
Fegie Yoanti Wattimena
Information Systems Study Program, Faculty of Science & Technology, Universitas Ottow Geissler Papua, Jayapura City, Papua Province, Indonesia
Yulianto Umar Rofi'i
Digital Business Study Program, Institut Teknologi dan Bisnis Muhammadiyah Bali, Jembrana Regency, Bali Province, Indonesia
Munawir
Digital Business Study Program, Institut Teknologi dan Bisnis Muhammadiyah Bali, Jembrana Regency, Bali Province, Indonesia
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