Rancang Bangun Sistem Rekomendasi Wisata di Pulau Bawean Menggunakan Metode Item-based Collaborative Filtering Berbasis Website. (Designing a Travel Recommendation System on Bawean Island Using Item-based Collaborative Filtering Method Based on Website).

Hatami, Mohammad (2024) Rancang Bangun Sistem Rekomendasi Wisata di Pulau Bawean Menggunakan Metode Item-based Collaborative Filtering Berbasis Website. (Designing a Travel Recommendation System on Bawean Island Using Item-based Collaborative Filtering Method Based on Website). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

This research aims to overcome the problem of lack of promotional information on tourist attractions on Bawean Island, which often makes it difficult for visitors to choose a destination that suits their interests. In this study, researchers will apply the Item-based Collaborative Filtering method to provide tourist attraction recommendations based on similarities between objects. The research steps include analyzing user needs, designing an easy-to-understand interface, implementing the Item-based Collaborative Filtering method, and testing system performance. With this method, it is expected that the visitor experience can be improved through recommendations that are more personalized and in accordance with their individual preferences. The results of this study show that this website functions well and get questionnaire results with a total of 89.3% of 34 users who strongly agree that this website helps them find tourist attraction recommendations. It is expected to make a positive contribution in increasing the utilization of the tourism potential of Bawean Island and providing practical solutions to problems faced by visitors. Further development is recommended to improve the interface (UI) and user experience (UX) to make it more comfortable. The addition of a rating filter feature based on time can also provide relevant information to users about the popularity of tourist destinations in a certain time range.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Recommendation System, Item-based Collaborative Filtering, Website
Subjects: G Geography. Anthropology. Recreation > GV Recreation Leisure
T Technology > T Technology (General)
Divisions: Fakultas Teknik > Program Studi Teknik Informatika
Depositing User: 1462000197 Mohammad Hatami
Date Deposited: 05 Sep 2001 15:26
Last Modified: 05 Oct 2001 19:56
URI: http://repository.untag-sby.ac.id/id/eprint/34231

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