Café Recommendation Using the Content-Based Filtering Method
DOI:
https://doi.org/10.51519/journalisi.v6i3.813Keywords:
Recommendation System, Content-Based Filtering, CafeAbstract
The coffee industry has experienced rapid growth over the last decade. In this research, the content-based filtering approach is employed to suggest cafes by analyzing the similarity of different features or attributes. The degree of similarity is influenced by the similarity of item profiles between cafes. CW Coffee & Eatery had the highest similarity value of 0.4802 because it found 16 item profiles that were similar to Cosan Seturan. In contrast, Kelanaloka has a very low similarity value of 0.1844, because only 7 similar item profiles were identified when compared. This research shows that content-based filtering methods can be effectively applied to cafe recommendation systems.
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References
M. N. H. Alvianto and S. Saifullah, “Sistem Pendukung Keputusan Pemilihan Cafe di Yogyakarta dengan Menggunakan Metode Simple Additive Weighting (SAW),” J. Innov. Inf. Technol. Appl. JINITA, vol. 2, no. 1, pp. 47–55, 2020.
S. Kurniawan, A. Putra, and A. Ependi, “Analisis Usability Aplikasi C-Access Commuterline Menggunakan System Usability Scale (Sus),” J. Syntax Admiration, vol. 4, no. 7, pp. 894–911, 2023.
H. R. Maryen, E. L. Tatuhey, and P. Hasan, “Sistem Pendukung Keputusan Rekomendasi Pemilihan Cafe di Jayapura Menggunakan Metode Moora,” Jutisi J. Ilm. Tek. Inform. Dan Sist. Inf., vol. 13, no. 1, pp. 515–527, 2024.
N. Hanin and A. Adi, “Sistem Pendukung Keputusan Pemilihan Cafe Bagi Mahasiswa Kota Pontianak Dengan Metode SAW,” J. Nas. Teknol. Dan Sist. Inf., vol. 9, no. 2, pp. 95–102, 2023.
B. Hermanto, “Sistem Rekomendasi Kedai Kopi dengan Metode Collaborative Filtering di Kota Yogyakarta Berbasis WEB,” 2020.
F. O. Isinkaye, Y. O. Folajimi, and B. A. Ojokoh, “Recommendation systems: Principles, methods and evaluation,” Egypt. Inform. J., vol. 16, no. 3, pp. 261–273, 2015.
A. Ningrum, “Content Based Dan Collaborative Filtering Pada Rekomendasi Tujuan Pariwisata Di Daerah Yogyakarta. Telematika, 16 (1), 44,” 2019.
R. Faurina and E. Sitanggang, “Implementasi Metode Content-Based Filtering dan Collaborative Filtering pada Sistem Rekomendasi Wisata di Bali.,” Techno Com, vol. 22, no. 4, 2023.
M. Alkaff, H. Khatimi, and A. Eriadi, “Sistem Rekomendasi Buku pada Perpustakaan Daerah Provinsi Kalimantan Selatan Menggunakan Metode Content-Based Filtering,” MATRIK J. Manaj. Tek. Inform. Dan Rekayasa Komput., vol. 20, no. 1, pp. 193–202, 2020.
S. A. Gunarto, E. S. Honggara, and D. D. Purwanto, “Website Sistem Rekomendasi dengan Content Based Filtering pada Produk Perawatan Kulit,” JUSTIN J. Sist. Dan Teknol. Inf., vol. 11, no. 3, pp. 399–404.
P. B. Thorat, R. M. Goudar, and S. Barve, “Survey on collaborative filtering, content-based filtering and hybrid recommendation system,” Int. J. Comput. Appl., vol. 110, no. 4, pp. 31–36, 2015.
U. S. Senarath, “Waterfall methodology, prototyping and agile development,” Tech Rep, pp. 1–16, 2021.
M. J. Pazzani, “A framework for collaborative, content-based and demographic filtering,” Artif. Intell. Rev., vol. 13, pp. 393–408, 1999.
Y. Sun and Y. Zhang, “Conversational recommender system,” presented at the The 41st international acm sigir conference on research & development in information retrieval, 2018, pp. 235–244.
S. Gharatkar, A. Ingle, T. Naik, and A. Save, “Review preprocessing using data cleaning and stemming technique,” presented at the 2017 international conference on innovations in information, embedded and communication systems (iciiecs), IEEE, 2017, pp. 1–4.
R. M. Furr, “A framework for profile similarity: Integrating similarity, normativeness, and distinctiveness,” J. Pers., vol. 76, no. 5, pp. 1267–1316, 2008.
A. Huang, “Similarity measures for text document clustering,” presented at the Proceedings of the sixth new zealand computer science research student conference (NZCSRSC2008), Christchurch, New Zealand, 2008, pp. 9–56.
M. Laaziri, K. Benmoussa, S. Khoulji, and M. L. Kerkeb, “A Comparative study of PHP frameworks performance,” Procedia Manuf., vol. 32, pp. 864–871, 2019.
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