Recommendation System for Selecting Brownies Cinta Menu Using Content-Based Filtering Method
DOI:
https://doi.org/10.70609/gtech.v8i4.5065Keywords:
Culinary business, Brownies Cinta, recommendation system, Content-Based Filtering, Cosine SimilarityAbstract
Culinary businesses in Indonesia, such as Brownies Cinta Karanganyar, face challenges in helping consumers choose products with the best taste. This study aims to implement a Brownies Cinta menu recommendation system using the Content-Based Filtering method with the cosine similarity algorithm. The system was developed through the SDLC Waterfall stages: planning, design, implementation, testing, and maintenance. The TF-IDF algorithm is used to calculate the initial value, which is then processed with cosine similarity to produce accurate recommendations. The test results show that the "Lapis Kukus Fruity (Regular)" and "Brownies Oven Almond (Regular)" menus have the highest cosine similarity values, reaching 0.950. In contrast, the D19 document with the lowest cosine similarity value is considered irrelevant. In conclusion, the developed content-based recommendation system can provide the best and most relevant recommendations to users. The use of the TF-IDF and cosine similarity algorithms has proven to be accurate, increasing consumer satisfaction in choosing products. This system helps Brownies Cinta consumers determine the products they want to buy, facilitating the menu selection process.
References
Az-zahra, F. (2021). Analisis Sentimen Pada Twitter Shopee Indonesia Menggunakan K-Nearest Neighbor Dengan Pembobot Term Frequency-Inverse Document Frequency (TF-IDF). 21.
Budiman, A. E., & Widjaja, A. (2020). Analisis Pengaruh Teks Preprocessing Terhadap Deteksi Plagiarisme Pada Dokumen Tugas Akhir. Jurnal Teknik Informatika Dan Sistem Informasi, 6(3), 475–488. https://doi.org/10.28932/jutisi.v6i3.2892
Dhery, H., Assyam, A., & Hasan, F. N. (2023). Analisis Sentimen Twitter Terhadap Perpindahan Ibu Kota Negara Ke IKN Nusantara Menggunakan Orange Data Mining. KLIK: Kajian Ilmiah Informatika Dan Komputer, 4(1), 341–349. https://doi.org/10.30865/klik.v4i1.957
Hartatik, H., Nurhayati, S. D., & Widayani, W. (2021). Sistem Rekomendasi Wisata Kuliner di Yogyakarta dengan Metode Item-Based Collaborative Filtering. Journal Automation Computer Information System, 1(2), 55–63. https://doi.org/10.47134/jacis.v1i2.8
Marga Putri, N. P. (2024). Analisis Faktor Penghambat Pengiriman Produk Brownies Cinta Ke Luar Pulau Jawa Studi Kasus : Brownies Cinta Karanganyar Tahun 2023. Jurnal Ekonomi Manajemen Dan Akuntansi, 2(1), 9–16.
Muhammad Yusuf Siregar, Ade Davy Wiranata, R. A. S. (2024). Analisis Sentimen Pada Ulasan Pengguna Aplikasi Streaming Vidio Menggunakan Metode Naïve Bayes. JATI (Jurnal Mahasiswa Teknik Informatika), 8(2), 2297–2302. https://doi.org/10.30865/klik.v4i5.1787
Muliawan, A., Badriyah, T., & Syarif, I. (2022). Membangun Sistem Rekomendasi Hotel dengan Content Based Filtering Menggunakan K-Nearest Neighbor dan Haversine Formula. Technomedia Journal, 7(2), 231–247. https://doi.org/10.33050/tmj.v7i2.1893
Nurwati, & Hasdar, M. (2021). Sifat Organoleptik Kue Brownies Dengan Penambahan Rumput Laut (Eucheuma cottonii). Journal of Food Technology and Agroindustry, 3(2), 1–7.
Oktaviana Yamin, V., Tenriawaru, A., Ode Saidi, L., Arviana Rahman, G., Ilmu Komputer, S., Matematika dan Ilmu Pengetahuan Alam, F., Halu Oleo Jl HEA Mokodompit, U., & Tenggara, S. (2023). Penerapan Naïve Bayes Classifier dengan Algoritma Nazief dan Adriani Untuk Deteksi Hoaks. 1(1), 1–5.
Oktavika, R. (2023). Sistem Rekomendasi Wisata Dengan Menggunakan Algoritma Collaborative Filtering. Teknologipintar.Org, 3(1), 1–15.
Permana, R., Abdilah, A., Fuad Nur Hasan, & Mahmud Syarif. (2023). Estimation Effort Pengembangan Software Inventory PT. Infinity Global Mandiri Menggunakan Metode Use Case Point. Jurnal RESTIKOM : Riset Teknik Informatika Dan Komputer, 5(2), 73–84. https://doi.org/10.52005/restikom.v5i2.144
Rahmawati, E. F., & Nurhadi. (2023). Pengaruh Atribut Produk, Harga dan Iklan Terhadap Perpindahan Merek pada Konsumen Viva Cosmetics di Surabaya. Jurnal Administrasi Bisnis, 13(1), 1–8. https://doi.org/10.35797/jab.13.1.1-8
Ramadhan, J. A., Haniva, D. T., & Suharso, A. (2023). Systematic Literature Review Penggunaan Metodologi Pengembangan Sistem Informasi Waterfall, Agile, dan Hybrid. JIEET : Journal Information Engineering and Educational Technology, 07(01), 36–42.
Septiani, D., & Isabela, I. (2022). Analisis Term Frequency Inverse Document Frequency (Tf-Idf) Dalam Temu Kembali Informasi Pada Dokumen Teks. SINTESIA: Jurnal Sistem Dan Teknologi Informasi Indonesia, 1(2), 81–88.
Susanto, M. R. R., Husni Thamrin, & Naufal Azmi Verdikha. (2023). Performance of Text Similarity Algorithms for Essay Answer Scoring in Online Examinations. Jurnal Teknik Informatika (Jutif), 4(6), 1515–1521. https://doi.org/10.52436/1.jutif.2023.4.6.1025
Widaningrum, I., Mustikasari, D., Arifin, R., Tsaqila, S. L., & Fatmawati, D. (2022). Algoritma Term Frequency-Inverse Document Frequency (TF-IDF) dan K-Means Clustering Untuk Menentukan Kategori Dokumen. Prosiding Seminar Nasional Sistem Informasi Dan Teknologi (SISFOTEK), 145–149.
Yuliani, M., & Durbin Hutagalung, D. (2023). Sistem Rekomendasi Webtoon dengan Menggunakan Metode Content-Based Filtering. Jurnal Ilmu Komputer Dan Science, 2(11), 2959–2964.
Zuhdiansyah, I., & Luthfiarta, A. (2024). Sistem Rekomendasi Pembelian Smartphone berbasis Algoritma K-Means dan Singular Value Decomposition. Jurnal Nasional Teknologi Dan Sistem Informasi, 10(1), 45–53. https://doi.org/10.25077/teknosi.v10i1.2024.45-53
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Fauziah Fanny, Rudi Susanto, Faulinda Ely Nastiti
This work is licensed under a Creative Commons Attribution 4.0 International License.
