• Ressa Priskila Universitas Palangka Raya
  • Nova Noor Kamala Sari Universitas Palangka Raya
  • Putu Bagus Adidyana Anugrah Putra Universitas Palangka Raya



Many housewives are still confused about what dishes they will cook with existing food ingredients. Most housewives get recipe ideas from the website. Recipes from the website have the advantage of being easily accessible, but the disadvantages are sometimes troublesome for users because they have to choose a recipe from which site because there are many sites that contain the same recipe, and most of the recipe websites on the internet do not have a feature to search recipes based on the ingredients they have. The aim of this research is to implement a content-based filtering method using TF-IDF and cosine similarity for a recipe recommendation system. The TF-IDF and cosine similarity models are used to find similarity values between material data in the database and the query entered by the user in the search form. The sample data used in this research is 30 recipe data points taken from the website As a result, this system displays recipe recommendations that match the query of ingredients inputted by the user on the search form, and based on the test results using root mean square error (RMSE), it can be said that the recommendation system with the content-based filtering method that has been implemented produces quite good recommendations with a value of 0.356359182.


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Februariyanti, H., Laksono, A. D., Wibowo, J. S., & Utomo, M. S. (2021). Implementasi Metode Collaborative Filtering Untuk Sistem Rekomendasi Penjualan Pada Toko Mebel. Jurnal Khatulistiwa Informatika, 9(1).

Putri, M. W., Muchayan, A., & Kamisutara, M. (2020). Sistem Rekomendasi Produk Pena Eksklusif Menggunakan Metode Content-Based Filtering dan TF-IDF. JOINTECS (Journal of Information Technology and Computer Science), 5(3), 229-236.

Larasati, F. B. A., & Februariyanti, H. (2021). Sistem Rekomendasi Product Emina Cosmetics Dengan Menggunakan Metode Content-Based Filtering. Jurnal Manajemen Informatika Dan Sistem Informasi, 4(1), 45-54.

Alkaff, M., Khatimi, H., & Eriadi, A. (2020). Sistem Rekomendasi Buku Menggunakan Weighted Tree Similarity dan Content Based Filtering. MATRIK J. Manajemen, Tek. Inform. dan Rekayasa Komput, 20(1), 193-202.

Christian, Y., & Kelvin, K. (2022). Rancang Bangun Aplikasi Kursus Online Berbasis Web Dengan Sistem Rekomendasi Metode Content-Based Filtering. Rabit: Jurnal Teknologi dan Sistem Informasi Univrab, 7(1), 23-36.

Nastiti, P. (2019). Penerapan Metode Content Based Filtering dalam Implementasi Sistem Rekomendasi Tanaman Pangan. Teknika, 8(1), 1-10.

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.

Shalannanda, W., Mulia, R. F., Muttaqien, A. I., Hibatullah, N. R., & Firdaus, A. (2022). Singular value decomposition model application for e-commerce recommendation system: Aplikasi model dekomposisi nilai tunggal untuk sistem rekomendasi e-commerce. JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga), 2(2), 103-110.

Wibisono, C., Haryadi, L. S., Widyaya, J. E., & Liliawati, S. L. (2021). Sistem Rekomendasi Suku Cadang Berdasarkan Item Based Filtering. Jurnal Teknik Informatika dan Sistem Informasi, 7(1).

Syah, R. D. (2020). Performa Algoritma User K-Nearest Neighbors pada Sistem Rekomendasi di Tokopedia. Jurnal Informatika Universitas Pamulang, 5(3), 302-306.

Khusna, A. N., Delasano, K. P., & Saputra, D. C. E. (2021). Penerapan User-Based Collaborative Filtering Algorithm. Matrik: Jurnal Manajemen, Teknik Informatika Dan Rekayasa Komputer, 20(2), 293-304.