An Android-Based User Recommendation System for Social Network Platform Using Collaborative Filtering Method on Youth Break the Boundaries Foundation
Sistem Rekomendasi Pengguna Aplikasi Jejaring Sosial Berbasis Android dengan Algoritma Cosine Similarity pada Youth Break the Boundaries Foundation
-
(1) * Suhendra
STIKI Malang, Indonesia
India
(2) Yekti Asmoro Kanthi STIKI Malang, Indonesia
Indonesia
(3) Arif Tirtana STIKI Malang, Indonesia
Indonesia
(*) Corresponding Author
Abstract
The popularity of social networking services has been increasing in recent years. Hundreds of millions of active users can pose a risk of information overload. These popular services have recommender systems that can capture user interests and provide users with potentially interesting information. It is different from the relatively new Youth Break the Boundaries (YBB) social networking application, it does not yet have complete features, let alone a complex recommender system which causes user interest in using the application is low. Implementing this system on the YBB application will affect the flow of the existing system so that a comprehensive update is needed. The development uses the cosine similarity algorithm on the application search page. It is proven to be able to provide recommendations for users with an accuracy rate of 0.92. With this system, users are helped in expanding their network with other users who have the same interests.
References
[2] X. Luo, C. Jiang, W. Wang, Y. Xu, J. H. Wang, and W. Zhao, “User behavior prediction in social networks using weighted extreme learning machine with distribution optimization,” Futur. Gener. Comput. Syst., vol. 93, pp. 1023–1035, Apr. 2019.
[3] J. Kim, T. Guo, K. Feng, G. Cong, A. Khan, and F. M. Choudhury, “Densely Connected User Community and Location Cluster Search in Location-Based Social Networks,” in Proceedings of the ACM SIGMOD International Conference on Management of Data, 2020, pp. 2199–2209.
[4] Y. Sun and Y. Zhang, “Conversational recommender system,” in 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018, 2018, pp. 235–244.
[5] X. Wang, Z. Xu, X. Xia, and C. Mao, “Computing user similarity by combining SimRank++ and cosine similarities to improve collaborative filtering,” Proc. - 2017 14th Web Inf. Syst. Appl. Conf. WISA 2017, vol. 2018-Janua, pp. 205–210, 2018.
[6] A. D. Putri and A. Susanto, “Sistem Rekomendasi Pertemanan berdasarkan Hobi menggunakan Metode Multicriteria Decision Making,” J. Inform. dan Rekayasa Perangkat Lunak, vol. 2, no. 1, p. 1, 2020.
[7] F. A. Fauzi, G. E. Putra, S. Supriyanto, N. A. Saputra, and T. Desyani, “Pengujian Terhadap Aplikasi Parking Management Menggunakan Metode Black-Box Berbasis Equivalence Partitions,” J. Teknol. Sist. Inf. dan Apl., vol. 3, no. 2, pp. 64–68, Apr. 2020.
Copyright (c) 2022 Suhendra, Yekti Asmoro Kanthi, Arif Tirtana
This work is licensed under a Creative Commons Attribution 4.0 International License.
