Refida Septiana Putri, Iqrom Danang Putra, Sitaresmi Wahyu Handani
Identifying facial skin type is a crucial first step in selecting appropriate skincare products, yet many individuals lack access to affordable dermatological consultations. This study developed a web-based expert system for facial skin type identification using the Certainty Factor (CF) method, implemented via the Laravel framework. The system diagnoses five skin types normal, dry, oily, combination, and sensitive based on 13 symptoms derived from dermatological literature. CF values were sourced from published studies and serve as the system's Knowledge Base. Users input their level of confidence regarding the symptoms they experience; these inputs are combined with expert CF values to calculate confidence scores for each skin type, with the highest-scoring type designated as the diagnosis result. The system also provides educational skincare articles tailored to each skin type. Development results demonstrate that the CF method effectively handles the subjectivity and uncertainty inherent in symptom-based diagnosis, enabling the system to serve as an initial screening tool for the public prior to seeking professional consultation.