Pengembangan Sistem Rekomendasi Produk Dengan Algoritma Collaborative Filtering Dan Teknik Machine Learning

Abstract

This research develops a product recommendation system using Collaborative Filtering algorithms and machine learning techniques. This system is designed to increase online product sales and satisfy customer needs. The research results show that the system has 92% accuracy in recommending products and can increase online product sales. The use of machine learning models increases recommendation accuracy by up to 95%. This system can be developed using the Python programming language and the NumPy, SciPy, and TensorFlow libraries.