IMPLEMENTASI METODE CONVOLUTIONAL NEURAL NETWORK
(CNN) UNTUK DETEKSI PENYAKIT PSORIASIS, RINGWORM DAN
SCABIES PADA KULIT MANUSIA
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Alipah, Devi Nur
Kuswardani, Dwina
Siregar, Riki Ruli Affandi
Kuswardani, Dwina
Siregar, Riki Ruli Affandi
Subject
Teknik Informatika
Datestamp
2023-06-21 02:57:00
Abstract :
Skin disease is a condition when the outer layer of the body experiences inflammation or irritation caused by bacteria, viruses, parasites, and fungi. Skin diseases are distinguished in several ways, depending on the infecting organism. This study aims to determine the classification of skin disease images in the detection of Psoriasis, Ringworm, and Scabies using the Convolutional Neural Network (CNN) method which is based on helping ordinary people in early screening of psoriasis, ringworm, and scabies skin diseases. Thus, a method is needed to identify the type of skin disease using an image processing system and artificial neural networks. The Convolutional Neural Network (CNN) method was used in this study, by detecting skin diseases Psoriasis, Ringworm, and Scabies with the Mobilenetv2 architecture as a result of making CNN models deployed into Mobile Applications. The training results in the study obtained the best accuracy of 75.00% while in the Confusion Matrix accuracy test obtained 74.33%.
Skin disease is a condition when the outer layer of the body experiences inflammation or irritation caused by bacteria, viruses, parasites, and fungi. Skin diseases are distinguished in several ways, depending on the infecting organism. This study aims to determine the classification of skin disease images in the detection of Psoriasis, Ringworm, and Scabies using the Convolutional Neural Network (CNN) method which is based on helping ordinary people in early screening of psoriasis, ringworm, and scabies skin diseases. Thus, a method is needed to identify the type of skin disease using an image processing system and artificial neural networks. The Convolutional Neural Network (CNN) method was used in this study, by detecting skin diseases Psoriasis, Ringworm, and Scabies with the Mobilenetv2 architecture as a result of making CNN models deployed into Mobile Applications. The training results in the study obtained the best accuracy of 75.00% while in the Confusion Matrix accuracy test obtained 74.33%.
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