Implementasi Algoritma Support Vector Machine (SVM) Untuk Deteksi Penyakit Kulit Berdasarkan Fitur ABCD RULE

Wibisono, Al Danny Rian (2024) Implementasi Algoritma Support Vector Machine (SVM) Untuk Deteksi Penyakit Kulit Berdasarkan Fitur ABCD RULE. Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

Skin diseases are a significant health problem that can cause symptoms such as itching, pain, numbness, and redness of the skin. These diseases can be caused by various factors such as viruses, fungi, or other microorganisms. According to data from the Surabaya Health Department website in 2019, the prevalence of skin and subcutaneous tissue diseases reached 4.53%, making it the sixth most common disease experienced by the community. This study aims to develop a prototype system for detecting skin diseases using a machine learning approach, specifically the Support Vector Machine (SVM) method with ABCD Rule features. The ABCD Rule features, consisting of Asymmetry, Border, Color, and Diameter, are important factors in identifying skin diseases. This study uses data from diseases such as Actinic keratosis, Dermatofibroma, Melanoma, Melanocytic nevus, and Vascular lesion for training and testing in the detection system. The final results of the study showed that the best testing scenario was obtained with a configuration of 80% training data and 20% test data using the RBF kernel with parameters C = 10 and gamma = 1, resulting in an accuracy of 86.42%, specificity of 96.60%, and sensitivity of 86.42%. A higher value of C than the gamma value makes the model more complex and minimizes errors on the training data, showing the high potential of this method in improving the quality of skin disease detection. Keywords: Skin Diseases, Machine Learning, Support Vector Machine (SVM), ABCD Rule Features, Disease Detection

Item Type: Thesis (Undergraduate)
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorMandyartha, Eka PrakarsaNIDN0725058805eka_prakarsa.fik@upnjatim.ac.id
Thesis advisorAl Haromainy, Muhammad MuharromNIDN0701069503muhammad.muharrom.if@upnjatim.ac.id
Subjects: L Education > L Education (General)
Q Science > Q Science (General)
Q Science > QA Mathematics
Q Science > QA Mathematics > QA76.6 Computer Programming
R Medicine > RL Dermatology
T Technology > T Technology (General)
Divisions: Faculty of Computer Science > Departemen of Informatics
Depositing User: Al Danny Al Danny Wibisono
Date Deposited: 16 Jul 2024 02:02
Last Modified: 16 Jul 2024 02:02
URI: https://repository.upnjatim.ac.id/id/eprint/26145

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