Penerapan Content-Based Filtering untuk Rekomendasi Film Netflix Berdasarkan Genre dan Klasifikasi Usia Penonton
DOI:
https://doi.org/10.55606/juitik.v5i3.1494Keywords:
Content-Based Filtering, Cosine Similarity, Movie, Recommendation System, TF-IDFAbstract
Recommendation systems have become an essential part of improving user experience, particularly in movie selection. With the ever-increasing number of movie titles, users often experience difficulty in determining which movies suit their interests and needs. Mismatches in movie selection, particularly in terms of age classification, can have negative impacts, particularly for children exposed to inappropriate content. Therefore, a recommendation system is needed that not only considers user preferences but also takes into account age restrictions. This study aims to build a movie recommendation system using a content-based filtering approach, considering two main aspects: genre and age classification. In its implementation, the Term Frequency-Inverse Document Frequency (TF-IDF) method is used as a word weighting technique for movie content information. This weighting is then used to calculate the level of similarity between movies using the Cosine Similarity method. This system is designed to be able to recommend relevant movies based on user preference input, such as the desired movie genre and the appropriate age classification. An evaluation was conducted to measure the extent to which the system is able to provide recommendations that match user preferences. The evaluation results show a similarity value of 1.00 for the genre aspect and 1.00 for the age classification aspect. This score indicates that the system successfully recommended highly relevant films that met the user's specified criteria. Therefore, the developed recommendation system effectively filters and suggests films that are not only content-appropriate but also safe for viewing based on the specified age restrictions.
References
Ardiansyah, R., Bianto, M. A., & Saputra, B. D. (2023). Sistem rekomendasi buku perpustakaan sekolah menggunakan metode content-based filtering. Jurnal CoSciTech (Computer Science and Information Technology), 4(2), 510–518. https://doi.org/10.37859/coscitech.v4i2.5131
Avinger, C. L. (2022). TV Parental Guidelines system. EBSCO. Retrieved July 29, 2025, from https://www.ebsco.com/research-starters/communication-and-mass-media/tv-parental-guidelines-system
Azizah, N., & Rozi, A. F. (2024). Sistem rekomendasi produk Somethinc menggunakan metode content-based filtering. Jurnal Teknologi Dan Sistem Informasi Bisnis, 6(3), 461–468. https://doi.org/10.47233/jteksis.v6i3.1411
Azri Saputra, J. M., Huizen, L. M., & Arianto, D. B. (2024). Sistem rekomendasi film pada platform streaming menggunakan metode content-based filtering. Jurnal Transformatika, 22(1), 10–21. https://doi.org/10.26623/transformatika.v22i1.7041
Hadi, G. N. (2019). Sistem rekomendasi film menggunakan metode content-based filtering. Skripsi. http://e-journal.uajy.ac.id/7244/4/3TF03686.pdf
Insan, R., Siagian, P., Khoiriah, N., Priscilia, S. A., Perdana, A., & Komputer, I. (2025). Penerapan machine learning untuk rekomendasi film berdasarkan preferensi pengguna. JATI (Jurnal Teknik Informatika), 9(4), 5658–5662. https://doi.org/10.36040/jati.v9i4.13884
Ismatun Nisak, I., Mukarromah, I., Aditama, L. M., & Zulfahmi, M. N. (2024). Pentingnya filterisasi konten dewasa pada perkembangan sosial emosional anak sekolah dasar. Jurnal Bintang Pendidikan Indonesia, 3(1), 199–209. https://doi.org/10.55606/jubpi.v3i1.3580
Nastiti, P. (2019). Penerapan metode content based filtering dalam implementasi sistem rekomendasi tanaman pangan. Teknika, 8(1), 1–10. https://doi.org/10.34148/teknika.v8i1.139
Rizky, M. Y., & Stellarosa, Y. (2019). Preferensi penonton terhadap film Indonesia. Communicare: Journal of Communication Studies, 4(1), 15. https://doi.org/10.37535/101004120172
Rochmad Wahono, A., Saputra, B. A., & Rahman, F. F. (2024). Sistem rekomendasi film menggunakan metode content-based filtering dan algoritma K-Nearest Neighbors (KNN). Prosiding Seminar Nasional Teknologi Informasi dan Bisnis, 1–6. https://doi.org/10.47701/senatib.v4i1.3994
Rusnawati, R. (2021). Efektivitas sensor mandiri pada orang tua terhadap tontonan anak usia 2–6 tahun. JURNAL HURRIAH: Jurnal Evaluasi Pendidikan dan Penelitian, 2(4), 108–113. https://doi.org/10.56806/jh.v2i4.37
Safitri, J., Atina, V., & Sudibyo, N. A. (2024). Rancang bangun sistem rekomendasi pemilihan drama Korea dengan metode content-based filtering. Infotech, 5(2), 175–189. https://doi.org/10.37373/infotech.v5i2.1235
Salim, E., Pragantha, J., & Manatap, D. L. (2021). Perancangan sistem rekomendasi film menggunakan metode content-based filtering. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 5(6), 2188–2199. https://lintar.untar.ac.id/repository/penelitian/buktipenelitian_10390001_7A281222103549.pdf
Shafina, G. (2023, July 19). Jumlah pelanggan layanan streaming Indonesia kian meningkat. GoodStats Data. Retrieved July 29, 2025, from https://data.goodstats.id/statistic/jumlah-pelanggan-layanan-streaming-indonesia-kian-meningkat-s2q42
Sudarsono, B. G., Leo, M. I., Santoso, A., & Hendrawan, F. (2021). Analisis data mining data Netflix menggunakan aplikasi Rapid Miner. JBASE - Journal of Business and Audit Information Systems, 4(1), 13–21. https://doi.org/10.30813/jbase.v4i1.2729
Sumarlin, E. W., Hansun, S., & Wiratama, Y. W. (2016). Rancang bangun aplikasi rekomendasi film dengan menggunakan algoritma Simple Additive Weighting. Jurnal Informatika, 10(2), 1244–1250. https://doi.org/10.26555/jifo.v10i2.a5066
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Jurnal Ilmiah Teknik Informatika dan Komunikasi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
