Ikhsan, Muhammad (2020) DETEKSI JENIS JERAWAT MENGGUNAKAN METODE GRAY LEVEL CO-OCCURENCE MATRIKS DAN JARINGAN SARAF TIRUAN. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
Acne is a part of various skin disorders that are almost similar to each other. Therefore, it needs to be classified to distinguish them. The severity of acne can cause emotional distress to hurt the skin. Some types of acne have different textures. These textures can be classified into types of acne. With digital image processing, a pimple image is extracted, and its texture features are then analyzed and classified to identify the type of acne. This study used five types of acne images, namely blackheads, whiteheads, cysts, pustules, and papules—the feature extraction method used to identify each type of acne on the image. The feature extraction method used was the Gray Level Co-occurrence Matrix (GLCM), while to classify an image in each patient using Backpropagation Neural Networks (ANN) to solve non-linear problems, including pattern recognition. This study obtained accuracy from the results of testing types of acne with a success rate of 76%. Keywords: Acne, Image Processing, GLCM, Artificial Neural Networks
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Teknik Elektro |
| Depositing User: | Kaprodi Teknik Elektro |
| Date Deposited: | 21 Mar 2020 04:47 |
| Last Modified: | 21 Mar 2020 04:47 |
| URI: | http://eprints.uty.ac.id/id/eprint/4749 |
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