HIBRID SISTEM REKOMENDASI MAKANAN SERTA MINUMAN DENGAN METODE CONTENT BASED FILTERING DAN COLLABORATIVE FILTERING STUDI KASUS PASAR PUNDENSARI

Nurrokhim, Fandi (2025) HIBRID SISTEM REKOMENDASI MAKANAN SERTA MINUMAN DENGAN METODE CONTENT BASED FILTERING DAN COLLABORATIVE FILTERING STUDI KASUS PASAR PUNDENSARI. S1 thesis, Universitas PGRI Madiun.

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Abstract

Pasar Pundensari is a traditional culinary destination that features a unique transaction system using bamboo sticks. However, the menu selection process is still manual, which makes it difficult for visitors to choose food that matches their preferences. This research develops a technology-based food recommendation system using Content-Based Filtering (CBF) and Collaborative Filtering (CF) methods. The CBF method analyzes menu similarity based on ingredients and categories using TF-IDF and Cosine Similarity, while the CF method identifies preference patterns based on other users' selection history. Data was collected through direct observation of the available menu at Pasar Pundensari. The system evaluation was conducted using accuracy, precision, recall, and F1-score metrics, showing that the hybrid method yields better recommendation accuracy compared to using individual methods. This system assists visitors in receiving relevant recommendations, facilitates efficient food selection, and enhances their culinary experience.

Item Type:	Thesis/Skripsi/Tugas Akhir (S1)
Kata Kunci:	Recommendation system, Hybrid Content-Based Filtering, Collaborative Filtering, TF-IDF, Cosine Similarity, Jaccard Similarity
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Teknik Informatika
Depositing User:	FANDI NURROKHIM FANDI
Date Deposited:	12 Aug 2025 01:37
Last Modified:	12 Aug 2025 01:37
URI:	http://eprint.unipma.ac.id/id/eprint/3426

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