KLASIFIKASI PENYAKIT KULIT MENGGUNAKAN ARTIFICIAL NEURAL NETWORK BACKPROPAGATION
| Main Author: | Respati, Rio |
|---|---|
| Format: | Thesis NonPeerReviewed Book |
| Bahasa: | ind |
| Terbitan: |
, 2015
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| Subjects: | |
| Online Access: |
https://eprints.untirta.ac.id/9379/1/KLASIFIKASI%20PENYAKIT%20KULIT%20MENGGUNAKAN%20ARTIFICIAL%20NEURAL%20NETWORK%20BACKPROPAGATION%20%282%29.pdf https://eprints.untirta.ac.id/9379/ https://ft.untirta.ac.id |
Daftar Isi:
- Skin disease is a disease that is easily found in Indonesia. Types of skin disease in Indonesia are also very diverse ranging from mild skin diseases such as skin fungus, ringworm and scabies through skin disease that is dangerous as melanoma skin cancer. Causes of skin diseases can be fungi, bacteria and viruses. Rapid spread of skin disease largely caused by a infectious diseases. This research aims to help the doctors to perform the classification of skin diseases by using Artificial Neural Network Backpropagation. This research is divided into two classes, namely Tinea Corporis and Herpes Zoster. There are two processes in Backpropagation ANN method, namely the training phase and testing phase. Then stages of feature extraction used to obtain the mean, standard deviation, kurtosis, skewness, entrophy and variance of the histogram of color, grayscale and histogram levels of saturation. Furthermore method of backpropagation ANN perform image classification of skin cancer according to each class. The results of image classification of skin diseases Tinea Corporis obtained accuracy rate 70% while for the skin disease Herpes Zoster obtained accuracy rate 70%. Keywords: skin diseases, tinea corporis, herpes zoster, ANN, backpropagation, extraction of features, accuracy