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All Journal JURNAL TEKNIK INFORMATIKA DAN KOMPUTER
Madani, Rafika Aulia
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Computer Science & IT

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Klasifikasi Penyakit dan Kelainan Bentuk Kuku Manusia Menggunakan Convolutional Neural Network Madani, Rafika Aulia; Nunik Pratiwi
Jurnal Teknik Informatika dan Komputer Vol. 3 No. 2 (2024): Jurnal Teknik Informatika dan Komputer
Publisher : Universitas Muhammadiyah Prof. DR. HAMKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/jutikom.v3i2.16891

Abstract

Nails are one of the body parts that have an important role, because nails can provide signals of a disease starting from the color, shape, and size of the nails. This study aims to identify diseases and abnormalities of human nail shape using digital images. This study uses seven classes of diseases, namely beausline, clubbing, koilonychia, yellow nail, white nail, onychomycosis, and normal nail. To identify diseases and abnormalities of human nail shape, the method used is Convolutional Neural Network with VGG-16 architecture. The results obtained from this study are an accuracy of 92.9% from a total dataset that has been augmented as much as 3900 data, for an average precision measurement result of 86.1%, an average recall result of 85.8%, an average f-1 score result of 85.8%.
Co-Authors Nunik Pratiwi