KLASIFIKASI PENYAKIT KULIT MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK

Liliek Triyono, Afandi Nur Aziz Thohari, Idhawati Hestiningsih, Amran Yobioktabera

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%.


Keywords


classification; skin disease; convolutional neural network

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References


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