<![CDATA[Sometimes, someone underestimates to check up skin disease unless the disease has affected his face or body in severe condition. The checkup fees for skin diseases are relatively expensive because they require a specialist. While the reach of society, in general, is the lower community. The purpose of this study is to bridge the gap between the patient and the examination of the disease based on the patient's skin image. The methods used in feature extraction and classification are Linear Discriminant Analysis LDA and Euclidean Distance respectively. LDA performs image feature extraction through a matrix operation process and distinguishing features in the same class and different classes. Classification will give the output of disease: abscess, eczema, ringworm, and urticaria. The accuracy results obtained are 80%. The next research is on adding features in the form of skin color so that it can be an input feature in the image as well as to improve its performance in the future. This application can be an alternative initial checkup for patients. It will detect the type of skin disease be suffered before consulting an expert.]]>
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