Mobile-Based Decision Support System for Recommending Tourism Attraction Using MAGIQ-ARAS Methodology

Abstract

Tourism in Bali faces challenges such as overcrowding, poor management, and diverse visitor preferences, which hinder effective decision-making for tourist destinations. This study introduces an Android-based DSS using the MAGIQ-ARAS. The MAGIQ method simplifies the weighting process, while the ARAS method evaluates alternatives to produce utility-based rankings. Together, MAGIQ-ARAS provide a structured approach for generating tourist recommendations tailored to user preferences. The research follows a combination of the CRISP-DM framework for data preparation and the Waterfall Model for system development. Field studies, interviews, and literature reviews informed the design of a mobile application that integrates MAGIQ and ARAS. Black-box testing verified functionality, and accuracy testing using a confusion matrix evaluated the alignment between recommendations and user preferences. The results demonstrate the system's effectiveness, achieving 90% accuracy in matching recommendations with user preferences. Black-box testing confirmed that all features, including preference weighting and interactive navigation, operated as intended. The system simplifies MCDM and enhances user satisfaction through its efficient and user-friendly interface. The study concludes that the MAGIQ-ARAS-based mobile application offers a reliable solution for tourist recommendations. Future work should explore real-time data integration and expand application to other tourism regions to enhance adaptability and usability.