<![CDATA[Stroke is a central nervous system disorder that ranks among the leading causes of disability and mortality worldwide, including in Indonesia. Early diagnosis plays a critical role in reducing the risk of severe complications. However, in practice, the initial diagnostic process is often hindered by uncertainty in symptom interpretation and the limited ability of medical personnel to provide objective assessments. To address this issue, this study developed a web-based expert system designed to assist in the early detection of stroke using the Certainty Factor (CF) method. This method was selected for its effectiveness in handling uncertainty by calculating confidence values based on a combination of MB (Measure of Belief) and MD (Measure of Disbelief), adjusted according to user input. The system was built using PHP programming language and MySQL database, allowing flexible access and multi-user support for both administrators and healthcare providers. Testing results indicate that the system can generate predictive diagnosis outcomes with a confidence limit 30%, in accordance with the internal policy of pondok aren regional hospital to ensure that the system functions solely as a screening tool. The system achieved an accuracy rate of 27% in testing, and all features operated as expected based on black-box testing, indicating thet it is suitable for use as an early diagnosis support tool. Therefore, this system is expected to assist healthcare professionals at pondok aren regional hospital in conducting initial stroke assessments digitally, quickly, and in a structured manner.]]>
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