Predictive analytics for sustainable tourism development: a data-driven approach

Abdul Mohaimin, Irfan Qayyim and Mohd Marzuki, Aida Najihah and Hassan, Raini (2025) Predictive analytics for sustainable tourism development: a data-driven approach. International Journal on Perceptive and Cognitive Computing, 11 (1). pp. 135-147. E-ISSN 2462-229X

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Abstract

Tourism plays a significant role in Malaysia's economic and social development, with efforts increasingly aligned to Sustainable Development Goals (SDGs), particularly SDG 8 (Decent Work and Economic Growth). This project addresses the lack of predictive analytics for sustainable tourism by employing a structured methodology encompassing data collection and preparation, exploratory data analysis (EDA), descriptive and predictive analytics, and feature engineering to identify key factors influencing sustainable tourism in Malaysia. The results show trends and patterns in tourism that inform the development of robust machine learning models to forecast sustainable tourism outcomes, in which 92% and 100% accuracy were achieved with Gradient Boosting and Support Vector Machine respectively. These models aim to support data-driven decision-making and promote long-term sustainability in Malaysia's tourism industry.

Item Type:	Article (Journal)
Uncontrolled Keywords:	predictive analytics, sustainable tourism, machine learning, data science, Malaysia
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Dr. Raini Hassan
Date Deposited:	10 Feb 2025 14:26
Last Modified:	10 Feb 2025 14:26
URI:	http://irep.iium.edu.my/id/eprint/119284

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