Respati, Rio (2015) KLASIFIKASI PENYAKIT KULIT MENGGUNAKAN ARTIFICIAL NEURAL NETWORK BACKPROPAGATION. S1 thesis, Universitas Sultan Ageng Tirtayasa.
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KLASIFIKASI PENYAKIT KULIT MENGGUNAKAN ARTIFICIAL NEURAL NETWORK BACKPROPAGATION (2).pdf - Published Version Restricted to Registered users only until 2015. Download (8MB) |
Abstract
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
| Item Type: | Thesis (S1) | ||||||
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| Additional Information: | Penyakit kulit merupakan penyakit yang mudah ditemukan di Indonesia. Jenis penyakit kulit di Indonesia juga sangat beragam mulai dari penyakit kulit yang ringan seperti panu, kadas, dan kurap sampai penyakit kulit yang berbahaya seperti kanker kulit melanoma. Penyebab penyakit kulit dapat berupa jamur , bakteri maupun virus. Penyebaran penyakit kulit yang cepat sebagian besar diakibatkan oleh penyakit menular. Penelitian ini bertujuan untuk membantu pihak dokter untuk melakukan klasifikasi penyakit kulit dengan menggunakan metode Artificial Neural Network Backpropagation. Penelitian ini dibagi menjadi dua kelas yaitu Tinea Corporis dan Herpes Zoster. Terdapat dua proses dalam metode ANN Backpropagation, yaitu tahap pelatihan dan tahap pengujian. Kemudian tahap ekstraksi fitur digunakan untuk mendapatkan nilai mean, standard deviation, kurtosis, skewness, entrophy dan variance dari histogram warna, grayscale dan histogram tingkat saturasi. Selanjutnya metode ANN backpropagation melakukan klasifikasi citra kanker kulit menurut kelasnya masing-masing. Hasil klasifikasi citra penyakit kulit Tinea Corporis didapatkan tingkat akurasi sebesar 70 % sedangkan untuk penyakit kulit Herpes Zoster didapatkan tingkat akurasi sebesar 70%. Kata kunci: Penyakit kulit, tinea corporis, herpes zoster, ANN, backpropagation, ekstrasi fitur, akurasi. | ||||||
| Uncontrolled Keywords: | Kata kunci: Penyakit kulit, tinea corporis, herpes zoster, ANN, backpropagation, ekstrasi fitur, akurasi. Keywords: skin diseases, tinea corporis, herpes zoster, ANN, backpropagation, extraction of features, accuracy. | ||||||
| Subjects: | T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | 03-Fakultas Teknik 03-Fakultas Teknik > 20201-Jurusan Teknik Elektro |
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| Depositing User: | Perpustakaan Pusat | ||||||
| Date Deposited: | 03 Dec 2021 14:09 | ||||||
| Last Modified: | 03 Dec 2021 14:09 | ||||||
| URI: | http://eprints.untirta.ac.id/id/eprint/9379 |
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