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All Journal Pixel : Jurnal Ilmiah Komputer Grafis
Alfarrel, M. Riza
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Sistem Rekomendasi Snack and Beverages Menggunakan Metode Item Based Collaboration Filtering Alfarrel, M. Riza; Wina Witanti; Edvin Ramadhan
Pixel :Jurnal Ilmiah Komputer Grafis Vol. 18 No. 2 (2025): Pixel :Jurnal Ilmiah Komputer Grafis dan Ilmu Komputer
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/pixel.v18i2.3319

Abstract

In today's digital era, recommendation systems have become an integral part of supporting consumer purchasing decisions, including in the food and beverage industry. This study aims to develop a product recommendation system for snacks and beverages using the item-based collaborative filtering method. This method was chosen due to its ability to handle large-scale user and product data, as well as its efficiency in providing relevant recommendations based on user consumption patterns. In this study, the system calculates the average user rating and implements   Cosine Similarity to measure the similarity between products, resulting in more accurate recommendations. The system also evaluates the accuracy of recommendations using the Mean Absolute Error (MAE) metric. Based on the results obtained, which is 0.285403 for the average error on 17 items, the developed recommendation system can improve consumers' shopping experience, help them find products that suit their tastes, and support the sales of snacks and beverages products in the market
Co-Authors Edvin Ramadhan Wina Witanti