Sistem Rekomendasi Produk Menggunakan Metode User-Based Collaborative Filtering Pada Digital Marketing

Satia Suhada (Program Studi Sistem Informasi, Universitas Bina Sarana Informatika, Sukabumi, Indonesia)
Saeful Bahri (Program Studi Ilmu Komputer, Universitas Bina Sarana Informatika, Sukabumi, Indonesia)
Setyo Bagus Nugraha (Program Studi Ilmu Komputer, Universitas Bina Sarana Informatika, Sukabumi, Indonesia)
Taufik Hidayatulloh (Program Studi Sistem Informasi, Universitas Bina Sarana Informatika, Sukabumi, Indonesia)
Dede Wintana (Universitas Bina Sarana Informatika)

Journal of Information Technology
Vol 11 No 1 (2023): J-Intech : Journal of Information and Technology

The recommendation system has been implemented in digital marketing used in marketing products and services. The recommendation system is used to provide offers of goods and services in accordance with customer habits and interests in the proposed products and services, but in practice the right product offering for customers leads to the idea of developing a product recommendation system. Purchase data obtained from customers can be used to analyze customer needs and product preferences. In the recommendation system, Collaborative Filtering is one of the most commonly used algorithms. The purpose of this study is to find out how accurate the recommendation system is based on the purchase of similar goods between consumers using User-based Collaborative Filtering. Based on the results of the study, User-based Collaborative Filtering using Cosine Similarity calculations can be applied and produce 10 product recommendations with an RMSE value of 0.9.