KLASIFIKASI PENYAKIT KULIT MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK
Abstract
Indonesia is a country with a tropical and humid climate. This climate makes the majority of Indonesia's population suffer from skin diseases caused by fungi. There are three types of skin diseases that many Indonesians suffer from, namely tinea versicolor, ringworm, and scabies. The majority of Indonesian people do not know the patterns and symptoms of these three diseases. Therefore, in this study a system was created that can classify tinea versicolor, ringworm, and scabies. Classification of skin diseases is done by applying artificial intelligence technology, namely Convolutional Neural Network (CNN). The dataset used as input was taken from google image and the dermet.com website. After going through the training process, the machine learning model has an accuracy of 96,75%. The model that has been obtained is then tested using test data and the accuracy of the test data is 91,67%.
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Deriyanthi, dr. D. (2021). 7 Penyakit Kulit yang Sering Diidap Orang Indonesia. https://www.gooddoctor.co.id/hidup-sehat/penyakit/penyakit-kulit-indonesia/
Hanin, M. A., Patmasari, R., & Nur, R. Y. (2021). Sistem klasifikasi penyakit kulit menggunakan convolutional neural network ( cnn ) skin disease classification system using convolutional neural network ( CNN ). In e-Proceeding of Engineering (Vol. 8, Issue 1).
Izzati Saila Hafsah, P. A. (2015). Deteksi Otomatis Penyakit Kulit Menggunakan Algoritma Naive Bayes (Issue 5).
Kemenkes RI. (2019). Profil Kesehatan Indonesia Tahun 2019. In Kementrian Kesehatan Repoblik Indonesia (Vol. 42, Issue 4).
Lotter, W., Sorensen, G., & Cox, D. (2017). A multi-scale CNN and curriculum learning strategy for mammogram classification. International Workshop on Deep Learning in Medical Image Analysis, 10553 LNCS, 169–177. https://doi.org/10.1007/978-3-319-67558-9_20
Radityastuti, R., & Anggraeni, P. (2017). Karakteristik Penyakit Kulit Akibat Infeksi di Poliklinik Kulit Dan Kelamin RSUP Dr. Kariadi semarang Periode Januari 2008 – Desember 2010. Media Medika Muda, 2(2), 137–142.
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