<![CDATA[Skin diseases in humans are disorders that affect the outermost layer of the body, characterized by symptoms such as itching, redness, and skin infections. These conditions may be caused by exposure to sunlight, viral infections, weakened immune systems, as well as the presence of fungi, bacteria, or parasites. This study aims to develop an expert system capable of diagnosing skin diseases based on the symptoms experienced by patients, using the Certainty Factor (CF) method. The Certainty Factor method itself is a technique used to measure the degree of uncertainty in knowledge-based systems, allowing for more accurate diagnostic outcomes. The system was tested using 100 test data entries encompassing various types of skin diseases, including morbus hansen, herpes zoster, contact dermatitis, tinea versicolor, tinea corporis, scabies, and psoriasis vulgaris. Each diagnosis is accompanied by a CF value that indicates the probability or confidence level. The results of the system testing showed an accuracy rate of 100%. With this optimal accuracy, the expert system is expected to serve as an early detection tool for skin diseases, providing reliable initial diagnoses and supporting treatment decision-making.]]>
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