@thesis{thesis,
		author={Alipah  Devi Nur and Kuswardani  Dwina and Siregar  Riki Ruli Affandi},
		title ={IMPLEMENTASI METODE CONVOLUTIONAL NEURAL NETWORK
(CNN) UNTUK DETEKSI PENYAKIT PSORIASIS, RINGWORM DAN 
SCABIES PADA KULIT MANUSIA},
		year={2022},
		url={http://156.67.221.169/5794/},
		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%.}
		}