<![CDATA[ Stress is a condition commonly experienced by university students due to academic demands, lifestyle, and daily activities. Poorly managed stress can negatively affect students’ physical and psychological well-being. This study aims to develop a web-based expert system to assist in the early detection of students’ stress levels using the Certainty Factor method. The symptom data were compiled based on Hans Selye’s stress theory under expert guidance, while the expert Certainty Factor values for each symptom were obtained through consultation with a psychologist. The system was developed using PHP programming language and MySQL database. The detection process is performed by processing the users’ confidence levels toward the symptoms along with the expert confidence values using the Certainty Factor method to determine three stress categories: mild, moderate, and severe. The calculation simulation resulted in Certainty Factor values of 0.50 for mild stress, 0.52 for moderate stress, and 0.18 for severe stress, resulting in a moderate stress detection. Black-box testing was conducted using 19 scenarios covering the functions of the user and admin pages, and all scenarios were successfully executed as expected, resulting in a 100% success rate. The system also provides recommendations related to lifestyle based on the detection results. Based on these results, the system can be used as a supporting tool to assist university students in conducting early stress detection independently.]]>
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