The skin is the largest organ of the body and functions as a biologically active barrier. However the threat of disease is unavoidable, one of which is skin cancer. The main causative factor for skin cancer is ultraviolet radiation which is a strong carcinogen. Indonesian health profile reported that expert medical numbers are unevenly distributed, particularly in rural areas with substandard healthcare facilities. This is inversely proportional to the number of skin cancer cases especially in countries with high levels of sun exposure. The application of artificial intelligence technology may prove to be a significant breakthrough, potentially assisting medical personnel in providing a second opinion. Through this study, an artificial intelligence system is designed using the Support Vector Machine (SVM) algorithm that will assist medical personnel in identifying the type of skin cancer. The performance of the SVM system will be evaluated using the evaluation parameters to see which kernel provides optimal results in identifying image data of skin cancer patients. The study begins with data acquisition and processing used to improve desmoscopy image quality. The combination of fractal and Gray Level Co-occurrence Matrix (GLCM) is used as feature extraction and Support Vector Machine (SVM) algorithm as identification algorithm. Based on the research results, the system performance using only the fractal method does not provide optimal results. Thus, with the addition methods to the preprocessing and feature extraction stages to optimize its performance obtained accuracy results in the polynomial kernel of 97.71% for training and 100% for testing.