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Eka Novita Shandra
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Pola Sidik Bibir Untuk Menentukan Jenis Kelamin Manusia Dengan Metode Gray Level Co-Occurrence Matrix Dan Support Vector Machine Eka Novita Shandra; Budi Darma Setiawan; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Identification is one way that can be done to recognize individual characteristics. Identification is needed to find out the clarity of personal identity, for both deceased and living people. In the world of forensic medicine, the role of identification is very important. Like fingerprints, lip prints also have unique characteristics for each individual. Lip prints can be used as a means to identify forensic and non-forensic cases. For nonforensic cases, lip prints can determine the sex of an individual. To help in the process of identifying gender based on lip prints, a classification system is needed that can classify the sex of women and men. The process begins with collecting lip print images which are then preprocessed and extracted texture features using the Gray Leveled Co-ocurrence (GLCM) method. There are 4 features that are used namely ASM, Contrast, Correlation and IDM with angles of 0o, 45o, 90o and 135o. Then the feature value is used by data for the training and testing process using the Support Vector Machine (SVM) method. The training data used in the test is 60 data. The results of this study have not provided a good level of accuracy because the system is only able to provide an accuracy of 51.4% by testing the GLCM parameter, namely distance = 1 and SVM parameters λ (lambda) = 0.5, C (complexity) = 1, constant (gamma) = 0.01, and itermax = 100.
Co-Authors Budi Darma Setiawan Yuita Arum Sari