<![CDATA[Stress is a psychological issue commonly experienced in society and can develop into more serious disorders if not properly addressed. However, access to professional services remains limited due to constraints such as time, cost, and unequal distribution of mental health professionals. Therefore, the objective of this study is to develop an expert system using a web-based Dempster-Shafer Theory (DST) approach capable of diagnosing stress types based on user-reported symptoms. DST enables the integration of various pieces of evidence to produce conclusions with measurable confidence levels. The system is equipped with functionality for managing symptom data, stress types, and the ability to provide diagnostic results accompanied by recommended solutions. Testing results demonstrated an accuracy level of 93.33%, placing this system in the "Good" category according to standard performance evaluation classifications. The implementation of DST has proven effective in managing data uncertainty and supporting confidence-based decision-making. This research contributes to the development of DST-based diagnostic technology that can be widely accessed via a web platform, providing a reliable alternative for early detection of stress types.]]>
Copyrights © 2025
