This study develops a web-based expert system for diagnosing hair damage using the Certainty Factor (CF) method to support early self-assessment and treatment recommendations. The knowledge base consists of five types of hair damage and five main symptoms with expert-validated belief weights. The CF method is applied to compute diagnostic confidence based on symptom combinations selected by users. System evaluation was conducted using test-case scenarios and numerical CF calculations. The results show that for three dominant symptoms, the system produces a CF value of 0.952, indicating a 95.2% confidence level. The novelty of this study lies in the expert-weighted knowledge modeling, transparent CF numerical analysis, and inference aggregation correction evaluation. The system can serve as an initial consultation tool before professional diagnosi.
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