Sistem Rekomendasi Games menggunakan Metode Item-based Collaborative Filtering berbasis Website

Fernando Febrianto(1*), Justinus Andjarwirawan(2), Rolly Intan(3),


(1) Program Studi Informatika
(2) Program Studi Informatika
(3) Program Studi Informatika
(*) Corresponding Author

Abstract


Item-based Collaborative Filtering is a method that is usually used for a Recommendation System based on the items that most users choose, because this method can recommend according to the tastes of most users who choose, this method is very effective in time to recommend an item in any form.

This study combines Fuzzy Similarity, Item-based Collaborative Filtering, and User-based to produce a recommendation, by calculating the similarity value using Fuzzy Similarity and User-based will make it easier to find the similarity value between users to be processed again using the Item-Based Collaborative Filtering method for recommendations that are suitable for users.

The results of this study are 10 Game Recommendations that are in accordance with the implementation of Item-based Collaborative Filtering, Fuzzy Similarity, and User-based which take from the most similar people by calculating the similarity value between users and take the game that is most chosen by users. and the recommendation system works, and from the survey results, it is found that people who try to enter this website do not feel confused about the User Interface, there are also many users who like to play games, and according to the survey, the accuracy rate is quite large.

Keywords


Item-Based Collaborative Filtering; User-Based Collaborative Filtering; game recommendation system; Fuzzy similarity

Full Text:

PDF

References


H. Maharani, 2015. “Rancangan Sistem Rekomendasi Game Dengan Model-Based Collaboration,”.

Norma. Y, Rahmi. R., and Ruliah, 2013. “Penerapan Algoritma Collaborative Filtering Untuk Rekomendasi Games Hardware,” J. Tek. Inform. dan Sist. Inf., vol. 2, no. 1, pp. 305–314,.

Andrew Hans Ritdrix P. W. W., 2018. “Sistem rekomendasi buku menggunakan metode item-based collaborative filtering skripsi,” vol. 9, pp. 24–32.

Boström P., and Filipsson M., 2017. “Comparison of User Based and Item Based Collaborative Filtering Recommendation Services,” KTH R. Inst. Technol., pp. 1–9.

Rolly I., and Mukaidono M., “Toward a Fuzzy Thesaurus Based on Similarity in Fuzzy Covering *,” vol. 8, no. 3, pp. 132–139.


Refbacks

  • There are currently no refbacks.


Jurnal telah terindeks oleh :