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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%.
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References
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References
Buyung, I., Munir, A. Q., S., N. W., & Listyalina, L. (2023). Identifying Types of Waste as Efforts in Plastic Waste Management Based on Deep Learning. Telematika: Jurnal Informatika Dan Teknologi Informasi, 20(3), 362–372. https://doi.org/10.31515/telematika.v20i3.10804
Efrian, M. R., & Latifa, U. (2022). Image Recognition Berbasis Convolutional Neural Network (Cnn) Untuk Mendeteksi Penyakit Kulit Pada Manusia. Power Elektronik : Jurnal Orang Elektro, 11(2), 276. https://doi.org/10.30591/polektro.v12i1.3874
Hadiyoso, S., & Aulia, S. (2022). Classification of Koilonychia, Beaus Lines, and Leukonychia based on Nail Image using Transfer Learning VGG-16. Jurnal Rekayasa Elektrika, 18(2), 109–114. https://doi.org/10.17529/jre.v18i2.25694
Hafifah, F., Rahman, S., & Asih, S. (2021). Klasifikasi Jenis Kendaraan Pada Jalan Raya Menggunakan Metode Convolutional Neural Networks (CNN). TIN: Terapan Informatika Nusantara, 2(5), 292–301. https://ejurnal.seminar-id.com/index.php/tin
Herdiana, E., Saniah, L., & Reyta, F. (2022). Deteksi Jenis Penyakit melalui Perubahan Warna Kuku dengan Teknik Image Processing. 5(1), 84–92.
Indi, T. S., & Gunge, Y. A. (2020). Early Stage Disease Diagnosis System Using Human Nail Image Processing. International Journal of Information Technology and Computer Science, 8(7), 30–35. https://doi.org/10.5815/ijitcs.2016.07.05
Irfansyah, D., Mustikasari, M., & Suroso, A. (2021). Arsitektur Convolutional Neural Network (CNN) Alexnet Untuk Klasifikasi Hama Pada Citra Daun Tanaman Kopi. Jurnal Informatika: Jurnal Pengembangan IT, 6(2), 87–92. https://doi.org/10.30591/jpit.v6i2.2802
Jupiter, F., Negara, E. S., Kunang, Y. N., & Herdiansyah, M. I. (2023). Implementasi Algoritma CNN dan YOLO untuk Mendeteksi Jenis Kendaraan pada Jalan Raya. Explore: Jurnal Sistem Informasi Dan Telematika, 14(2), 110. https://doi.org/10.36448/jsit.v14i2.3259
Kotta, C. R., Paseru, D., Sumampouw, M., Informatika, T., Katolik De La Salle Manado, U., & Kombos Manado -, K. I. (2022). Implementasi Metode Convolutional Neural Network untuk Mendeteksi Penyakit pada Citra Daun Tomat. Jurnal_Pekommas_Vol._7_No, 2, 123–132.
Kusumaningtyas, K., Habibi, M., Dwijayanti, I., Sumiyarini, R., Yani, A., Keperawatan, J., Achmad, Y., & Yogyakarta, I. (2023). Tweet Analysis of Mental Illness Using K-Means Clustering and Support Vector Machine Analisis Tweet Gangguan Kesehatan Mental Menggunakan K-Means Clustering dan Support Vector Machine. Jurnal Informatika Dan Teknologi Informasi, 20(3), 295–308. https://doi.org/10.31515/telematika.v20i3.9820
Lee, D. K., & Lipner, S. R. (2022). Optimal diagnosis and management of common nail disorders. Annals of Medicine, 54(1), 694–712. https://doi.org/10.1080/07853890.2022.2044511
Muthulatha, A., Tamilselvam, B., Shanmugam, S., & Pramodhini, S. (2021). Onychomycosis in onychodystrophy: a hospital-based clinico-mycological study. International Journal of Research in Dermatology, 7(3), 423. https://doi.org/10.18203/issn.2455-4529.intjresdermatol20211703
Nugraha, M. O., Purnamasari, R., & Aulia, S. (2022). Klasifikasi Penyakit Berdasarkan Warna Kuku Menggunakan Pengolahan Sinyal Digital (Classification of Diseases Based On Nail Color Using Digital Signal Processing). E-Proceeding of Engineering, 8(6), 3226–3239.
Nurkhasanah, & Murinto. (2021). Klasifikasi Penyakit Kulit Wajah Menggunakan Metode Convolutional Neural Network Classification of Facial Skin Diseases Using the Method of the Convolutional Neural Network. Sainteks, 18(2), 183–190. https://www.kaggle.com/datasets
Prawiratama, R. A. (2024). Design of a Generative AI Image Similarity Test Application and Handmade Images Using Deep Learning Methods. Telematika: Jurnal Informatika Dan Teknologi Informasi, 20(3), 326–342. https://doi.org/10.31515/telematika.v20i3.10096
Rismiyati, R., & Luthfiarta, A. (2021). VGG16 Transfer Learning Architecture for Salak Fruit Quality Classification. Telematika, 18(1), 37. https://doi.org/10.31315/telematika.v18i1.4025
Sasongko, T. B., Haryoko, H., & Amrullah, A. (2023). Analisis Efek Augmentasi Dataset dan Fine Tune pada Algoritma Pre-Trained Convolutional Neural Network (CNN). Jurnal Teknologi Informasi Dan Ilmu Komputer, 10(4), 763–768. https://doi.org/10.25126/jtiik.20241046583
Shaikh, Z. A., Hussain Shah, A., Kumar, A., Shaikh, I. A., Shaikh, B. A., & Kumar Ahuja, K. (2019). Skin manifestations in end stage renal disease patients on hemodialysis. The Professional Medical Journal, 26(10), 1678–1681. https://doi.org/10.29309/tpmj/2019.26.10.3390
Soğukkuyu, D. Y. C., & Ata, O. (2023). Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques. PeerJ Computer Science, 9, 1–17. https://doi.org/10.7717/peerj-cs.1533
Suartika E. P, I Wayan, Wijaya Arya Yudhi, S. R. (2021). Klasifikasi Citra Menggunakan Convolutional Neural Network (CNN) Pada Caltech 101. Jurnal Teknik ITS, 5(1), 76. http://repository.its.ac.id/48842/