Pengimplementasian Sistem Rekomendasi Musik Dengan Metode Collaborative Filtering

Abstract

Nowdays, Recommendation Systems are widely used on various platforms such as e-commerce, online cinemas, youtube, and online music streaming platforms. The Recommendation System is a machine learning algorithm that has goal to aim of providing predictions in the form of values or an action on an item that is given or given to a number of users, so that users can find new items that match what user likes and preferences of each user.

The Recommendation System has a variety of methods that can be implemented, one of which is the collaborative screening method. Collaborative filtering method works by providing predictions on a number of items to be given to the user based on the interaction value the user gives with these items. However, the collaborative filtering method itself has various types of algorithms which can be broadly divided into 2, namely the KNN algorithm and Matrix Factorization.

In this study, a collaborative filtering based music Recommendation System was implemented. Then conducted a study on the evaluation of the music Recommendation System using the KNN algorithm with a music Recommendation System using a Matrix Factorization algorithm.