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Firahmi Rizky
Universitas Muhammadiyah Sumatera Utara, Medan, Indonesia
Computer Science & IT Library & Information Science Mathematics

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Implementation of forward chaining in tourism recommendation selection expert system based on user preferences Firahmi Rizky
Jurnal Mandiri IT Vol. 12 No. 2 (2023): October: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v12i2.247

Abstract

Precise travel recommendations tailored to user preferences are a key element in enriching the travel experience. In this context, the Forward Chaining method in the User Preference-Based Travel Recommendation Selection Expert System offers a powerful and highly personalised approach. This article describes the implementation steps of the Forward Chaining method, which involves identification of user preferences, conversion of preferences to facts, initialisation of knowledge base, Forward Chaining process, evaluation of results, and customised travel recommendations. This method allows the system to dynamically respond to user preferences, generate accurate recommendations, and ensure that users are satisfied with their experience. However, some challenges such as privacy protection, complexity of user preferences, and knowledge base updates must be considered. Therefore, this article also discusses important implications of implementing the Forward Chaining method, including strict privacy protection, regular updates of the knowledge base, as well as the system's ability to learn from user feedback. In conclusion, the Forward Chaining method is a very useful approach in improving travel recommendation services tailored to user preferences, which can enrich the travel experience and result in higher satisfaction for users.
Implementation of forward chaining in tourism recommendation selection expert system based on user preferences Firahmi Rizky
Jurnal Mandiri IT Vol. 12 No. 2 (2023): October: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v12i2.247

Abstract

Precise travel recommendations tailored to user preferences are a key element in enriching the travel experience. In this context, the Forward Chaining method in the User Preference-Based Travel Recommendation Selection Expert System offers a powerful and highly personalised approach. This article describes the implementation steps of the Forward Chaining method, which involves identification of user preferences, conversion of preferences to facts, initialisation of knowledge base, Forward Chaining process, evaluation of results, and customised travel recommendations. This method allows the system to dynamically respond to user preferences, generate accurate recommendations, and ensure that users are satisfied with their experience. However, some challenges such as privacy protection, complexity of user preferences, and knowledge base updates must be considered. Therefore, this article also discusses important implications of implementing the Forward Chaining method, including strict privacy protection, regular updates of the knowledge base, as well as the system's ability to learn from user feedback. In conclusion, the Forward Chaining method is a very useful approach in improving travel recommendation services tailored to user preferences, which can enrich the travel experience and result in higher satisfaction for users.
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