PENERAPAN METODE COLLABORATIVE FILTERING DALAM SISTEM REKOMENDASI FILM

Arifin, Muhammad Fakhrul (2017) PENERAPAN METODE COLLABORATIVE FILTERING DALAM SISTEM REKOMENDASI FILM. S1 thesis, Universitas Pendidikan Indonesia.

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Official URL: http://repository.upi.edu

Abstract

Sistem rekomendasi adalah sistem yang dapat memberikan saran atau sugesti kepada user mengenai suatu informasi, contohnya film, buku, musik, berita dan lain-lain. Saran yang diberikan berdasarkan data yang didapatkan dari profil user seperti riwayat belanja, rating, dan lain-lain, sehingga saran yang diberikan dapat sesuai dengan selera dari pengguna tersebut. Dalam penelitian ini dijelaskan bagaimana penerapan salah satu metode yang digunakan dalam sistem rekomendasi, yaitu Collaborative Filtering. Collaborative Filtering memanfaatkan data rating yang diberikan oleh user terhadap suatu item, lalu data tersebut akan dibandingkan dengan pengguna lain untuk dicari kemiripannya. Penelitian ini dilakukan untuk mengukur tingkat akurasi prediksi dari sistem rekomendasi dengan menggunakan metode Collaborative Filtering. Penelitian ini menggunakan dataset MovieLens yang berisi data user sebanyak 943, data film sebanyak 1682 dan data rating sebanyak 100.000. Hasil dari penelitian ini nilai Mean Absolute Error (MAE) yang didapatkan adalah 0,821628506 dan nilai Root Mean Squared Error yang didapatkan adalah 0,984069686;--- Recommender system is a system that can provide suggestions to the user about an information, for example, movies, books, music, news, and others. Suggestions are given based on user profiles such as shopping history, ratings, etc. so that the suggestions provided are similar to the taste of the user. In this research is explained how the application of one of the methods used in the recommendation system, namely Collaborative Filtering. Collaborative Filtering utilizes the rating data provided by the user on an item, then the data will be compared with other users to look for resemblance. This research was conducted to measure the level of prediction accuracy of recommendation system by using Collaborative Filtering method. This study uses the MovieLens dataset which contains user data as much as 943, the movie data as much as 1682 and 100.000 rating data. The result of this research, the value Mean Absolute Error (MAE) obtained is 0,821628506 and Root Mean Squared Error value obtained is 0,984069686.

Item Type: Thesis (S1)
Additional Information: No Panggil : S KOM ARI p-2017; Pembimbing I. Lala Septem Riza, II. Eka Fitrajaya R; Nim: 1005289
Uncontrolled Keywords: sistem rekomendasi, collaborative filtering, machine learning, data mining, recommender system, collaborative filtering, machine learning, data mining
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Program Studi Ilmu Komputer
Depositing User: DAM staf
Date Deposited: 14 Dec 2018 07:53
Last Modified: 14 Dec 2018 07:53
URI: http://repository.upi.edu/id/eprint/32629

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