Implementation of the Simple Additive Weighting Method in a Decision Support System for Tourism Destination Selection

Abstract

Tourism destination selection is a complex decision-making process that involves multiple criteria, such as cost, accessibility, facilities, safety, and attractiveness. The rapid growth of tourism information available through digital platforms has increased the number of available alternatives, making it difficult for tourists to identify destinations that best match their preferences in a rational and transparent manner. This condition highlights the need for a structured decision support approach to reduce subjectivity and improve decision quality. Motivated by this challenge, this research proposes the implementation of a Decision Support System (DSS) for tourism destination selection using the Simple Additive Weighting (SAW) method as a multi-criteria decision-making technique. The proposed system enables users to evaluate tourism destinations based on user-defined criteria weights and normalized attribute values, allowing flexible and interpretable decision-making. The main contribution of this study lies in the practical integration of the SAW method into a functional DSS that emphasizes simplicity, transparency, and usability. The system is evaluated using real tourism destination data, and the results demonstrate that the SAW-based DSS is able to produce consistent and rational rankings aligned with the assigned criteria and weights. The evaluation confirms that destinations with superior overall performance achieve higher preference values, validating the effectiveness of the proposed approach. For future work, the system can be enhanced by incorporating hybrid decision-making methods, adaptive weighting mechanisms, and larger datasets to improve robustness, personalization, and scalability.