Case-Based Expert System for Diagnosing Scalp Disease
Abstract
Scalp disease is usually general in nature which tends to be ignored by sufferers because it is often considered harmless. This is a major factor slow to detect scalp disease so that if left untreated, the sufferer can be affected by acute scalp disease, which is very dangerous. This research builds an expert system to diagnose scalp disease earlier based on the symptoms that appear so that it is expected to assist medical personnel in identifying types of diseases, prevention solutions, and optimal treatment. This research used the Case-Based Reasoning (CBR) method, which combines similarity methods Similarity Measure introduced by Tversky with 10 types of diseases, 29 symptoms consisting of 110 cases of scalp disease. The results obtained in this study are a diagnosis of scalp disease, prevention solutions, and treatment. From the research, the conclusions are a diagnosis of scalp disease, prevention solutions, and treatment
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