Decision Support System in Smartwatch Selection Using The Weighted Product (WP) Method

Abstract

The advancement of information technology has significantly impacted daily life, including the development of smart devices such as smartwatches. Smartwatches are multifunctional devices capable of connecting to the internet and interacting with various electronic devices. However, the vast number of available options makes it difficult for consumers to choose the right smartwatch. This research proposes a web-based Decision Support System (DSS) utilizing the Weighted Product (WP) method to assist consumers in selecting the most suitable smartwatch. The WP method employs a weighted multiplication of ratings for each attribute to generate objective recommendations. Data collection was carried out through literature studies, questionnaires, and interviews. System analysis and design were followed by system testing using expert judgment, black-box testing, and the System Usability Scale (SUS). The evaluation results indicated that the DSS using WP achieved a 100% success rate in black-box testing, an SUS score of 75.25 (categorized as good), and expert judgment scores of 3.25, 3.5, and 3.75 (valid category). These results confirm that the proposed DSS is feasible for smartwatch selection.