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All Journal Sistemasi: Jurnal Sistem Informasi Jurnal Eksplora Informatika Jurnal Sisfokom (Sistem Informasi dan Komputer) Journal of Information Systems and Informatics JIKA (Jurnal Informatika) Information System Journal (INFOS) Intechno Journal : Information Technology Journal Scientific Journal of Informatics
arif nur rohman
UNIVERSITAS SEBELAS MARET
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Journal : Journal of Information Systems and Informatics

 1 
Application of Content-Based Filtering Method Using Cosine Similarity in Restaurant Selection Recommendation System Christyawan, Fajar; Rohman, Arif Nur; Hartanto, Anggit Dwi
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.806

Abstract

This research focuses on developing a restaurant recommender system designed to assist users in selecting restaurants based on preferences such as cuisine type and proximity, thereby enhancing the dining experience. The system employs a content-based filtering approach combined with the Cosine Similarity algorithm to calculate similarity values between restaurant addresses and categories, ensuring personalized and accurate recommendations. Data for the system was collected from TripAdvisor and Google Maps using a web scraping method, resulting in a comprehensive dataset that reflects a wide variety of dining options. An experiment involving 30 respondents was conducted to evaluate the system's performance under real-world conditions. The results demonstrated an accuracy rate of 88%, indicating that the recommender system effectively delivers highly relevant restaurant suggestions to users. These findings suggest that the system can serve as a valuable tool for culinary tourists and local residents, simplifying the process of discovering new dining experiences and aligning them with individual preferences.
Café Recommendation Using the Content-Based Filtering Method Wicaksono, Anggito Whiku; Rohman, Arif Nur; Hartanto, Anggit Dwi
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.813

Abstract

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.
Co-Authors Anggit Dwi Hartanto, Anggit Dwi Christyawan, Fajar Fajri, Ika Nur Fauzy, Marwan Noor Fiardin, Tsintani Tisaga Haz, Anando Muhammad Rahul Iedwan, Aisha Shakila Maulana, Handika Attha Mauliza, Nia Pratama, Akbar Rahmi, Alfie Nur Ramadhan, Ridhwan Shodiq Rayhan, Radhita Romadhon, Ibrahim Aji Fajar Sa'di, Ahmad Siska Siska Wicaksono, Anggito Whiku Yoga Pristyanto