Medical External Wound Image Classification Using Support Vector Machine Technique

Setya Mawarni, Syifa’ah and Murinto, Murinto and Sunardi, Sunardi (2023) Medical External Wound Image Classification Using Support Vector Machine Technique. [Artikel Dosen]

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Abstract

Diagnosis is an activity that refers to the examination of something. Diagnosis is often associated with
medical activities as a determinant of a person’s condition, in the health sector diagnosis means a procedure performed
by a doctor to determine a patient’s condition. Unfortunately, it is rare to diagnose disease using an object wound,
whereas if the wound is not treated immediately it can lead to more serious illnesses such as ulcers and tetanus or in
some cases it can cause infection which then becomes a complication, in the worst case amputation occurs. The skin
protects the body from various threats, the skin is also the first fortress for the body. Before implementing a prototype
external wound diagnosis, it is necessary to test the accuracy of the algorithm to be used so we know that the algorithm
used is suitable for the system to be developed. The algorithm that can be used for diagnosis or classification is the
Support Vector Machine or SVM which in the process goes through 3 stages, namely data collection, preprocessing,
and classification. This research obtained the results of feature extraction on the wound image test data using GLCM
with a contrast value of 0.0082, a correlation value of 0.9769, an energy value of 0.6391, and a homogeneity value of
0.9959 as well as the accuracy of using the SVM algorithm which was measured using a confusion matrix to get an
accuracy value of 96.39%, 93.06% precision, recall 92.85%, and F1-score 92.58%. The results of the accuracy of the
classification of external wound images using the SVM algorithm are 92.85%.

Item Type:	Artikel Dosen
Subjects:	T Technology > T Technology (General)
Divisi / Prodi:	Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Informatics Engineering (S1-Teknik Informatika)
Depositing User:	murinto murinto
Date Deposited:	27 Aug 2025 03:49
Last Modified:	27 Aug 2025 03:49
URI:	http://eprints.uad.ac.id/id/eprint/86682

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