The Integration of Ambient Intelligence with Serious Game for Recommendation System of Tourist Destinations Post-COVID-19 Pandemic

Arif, Yunifa Miftachul ORCID: https://orcid.org/0000-0002-2183-0762, Kurniawan, Fachrul ORCID: https://orcid.org/0000-0002-3709-8764, Nurhayati, Hani, Nugroho, Fresy ORCID: https://orcid.org/0000-0001-9448-316X, Faisal, Muhammad ORCID: https://orcid.org/0000-0003-4884-7254, Karami, Ahmad Fahmi and Afrah, Ashri Shabrina The Integration of Ambient Intelligence with Serious Game for Recommendation System of Tourist Destinations Post-COVID-19 Pandemic. In: The Spirit of Recovery IT Perspectives, Experiences, and Applications during the COVID-19 Pandemic. CRC Press, 2385 NW Executive Center Drive, Suite 320, Boca Raton FL 33431. ISBN 9781032363837 UNSPECIFIED : UNSPECIFIED.

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Abstract

The tourism sector faced significant challenges during the COVID-19 pandemic, necessitating innovative solutions for its recovery. This study introduces a novel approach by integrating Ambient Intelligence (AML) with a serious game to develop a tourism recommendation system. The proposed system employs a Multi-Criteria Recommender System (MCRS) for a known rating approach and Artificial Neural Network (ANN) for an unknown rating approach. Personal characteristics (PC) and destination attributes (DA) form the basis of data inputs, ensuring tailored recommendations that align with user preferences. The serious game leverages AML's adaptive features, creating an engaging environment where scenario choices dynamically reflect the system's recommendations. Experiments conducted in the Batu tourism area in Indonesia demonstrate the effectiveness of this system. Results reveal that the known rating approach achieves higher accuracy (74.3%) compared to the unknown rating approach (66.0%). This study highlights the potential of integrating AML with serious games to revitalize the tourism sector, offering personalized and adaptive recommendations to enhance user engagement and satisfaction.

Item Type:	Book Section
Keywords:	Ambient Intelligence;Serious Game;Tourism Recommendation;Multi-Criteria Recommender System
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Muhammad Faisal
Date Deposited:	04 Dec 2024 13:59

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