Sagara, Yosa (2020) IMPLEMENTASI ALGORITMA BACKPROPAGATION UNTUK SISTEM IDENTIFIKASI KEMATANGAN BUAH KAKAO. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
Cocoa fruit is one of the commodity plantations that has considerable potential in increasing the country's foreign exchange, and as a source of livelihood for 1.7 million farming families spread across various provinces in Indonesia where cocoa is used as a basis for making chocolate. Identification of the maturity of cocoa using the conventional method still lacks the accuracy of maturity. This occurs due to the subjective nature of the selection or lack of understanding of science in choosing ripe cacao. This study uses backpropagation artificial neural networks. Backpropagation artificial neural networks is one algorithm that is often used in solving complex problems. This system works with 4 process steps, namely preprocessing, training, presentation and prediction done on a desktop system. The system was trained and tested using 50 pictures of cacao fruits with 25 different maturity categories and 25 young categories. A total of 44 images of cacao fruit were used for the training process where the system could recognize 100% for trained cacao fruit and 83.3% for untrained cacao fruit. Keywords: Cocoa fruit, Image processing, Backpropagation
| 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 2020 05:35 |
| Last Modified: | 27 Mar 2020 05:35 |
| URI: | http://eprints.uty.ac.id/id/eprint/4922 |
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