📅 24 December 2025
DOI: 10.51903/pixel.v18i2.3319
Sistem Rekomendasi Snack and Beverages Menggunakan Metode Item Based Collaboration Filtering
JURNAL ILMIAH KOMPUTER GRAFIS
Universitas Sains dan Teknologi Komputer
📄 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
ℹ️ Informasi Publikasi
Tanggal Publikasi
24 December 2025
Volume / Nomor / Tahun
Volume 18, Nomor 2, Tahun 2025
📝 HOW TO CITE
Alfarrel, M. Riza; Alfarrel, M. Riza; Wina Witanti; Edvin Ramadhan, "Sistem Rekomendasi Snack and Beverages Menggunakan Metode Item Based Collaboration Filtering," JURNAL ILMIAH KOMPUTER GRAFIS, vol. 18, no. 2, Dec. 2025.
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