Fahmy, Muhammad (2021) Prediksi Jenis Kelamin Berdasarkan Citra Wajah dengan Metode LVQ (Learning Vector Quantization). Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
ABSTRACT This rapid development aims to help the performance every day, one of the technology that developed is digital imagery. With the existence of digital imagery, technology can help human work become more efficient, one of them is in the gender detecting. Many activities or activities that require a gender classification in their execution such as the determination of a person's fashion, a special women's car, toilets based on gender and many more that require a gender classification on their execution. This is what is a research reference for implementing and cooperating neural networks and digital imagery, in this study Learning Vector Quantization of neural Networks and Local Binary Pattern for image processing to detect gender based on facial imagery, the application uses two images as the initial weight, 16.592 as training data and 6264 as test data with 0.015 and 0.025 Learning rate. , the reduction of learning rate 0.01,0.001 and 0.0001 and epoch 100, with the best accuracy rate of 63,733%. Keywords: Gender, Local Binary Pattern, Learning vector Quantization (LVQ).
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 27 Mar 2021 03:24 |
| Last Modified: | 27 Mar 2021 03:24 |
| URI: | http://eprints.uty.ac.id/id/eprint/7203 |
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