Cahyaningtyas, Yovita (2025) Teknik Pengambilan Data dengan Metode Sampling untuk Pengolahan CNN dalam Sistem Deteksi Dini Penghitungan Benur Udang Vaname. Diploma thesis, Politeknik Negeri Jember.
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Abstract
Shrimp farming is one of the important sectors in the fisheries industry that has great potential to increase foreign exchange. Increasing the productivity of vaname shrimp (Litopenaeus vannamei) farming is highly dependent on the quality of the fry since the beginning of stocking. The manual counting process has various limitations, such as inaccuracy and delays in decision making. This research aims to develop a deep learning Convolutional Neural Network (CNN) model supported by data retrieval techniques with a sampling method followed by labeling using python to increase efficiency and accuracy in the early detection system for counting fry. The probability sampling method is used to obtain a representative dataset of the fry population in the culture pond. The sampling image data is then labeled and processed for CNN model training to recognize and count the number of fry automatically. Test results show that data labeling is able to improve object detection accuracy in CNN model training. This system is expected to be an applied solution in the automation of fingerlings monitoring that is efficient and adaptive to the aquaculture environment.
| Item Type: | Thesis (Diploma) | ||||||
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| Uncontrolled Keywords: | Vaname shrimp farming, Sampling, detection system, python, Convoluitonal Neural Network (CNN). | ||||||
| Subjects: | 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 457 - Teknik Komputer 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 458 - Teknik Informatika 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 459 - Ilmu Komputer 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 462 - Teknologi Informasi |
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| Divisions: | Jurusan Teknologi Informasi > Prodi D3 Teknik Komputer > Tugas Akhir | ||||||
| Depositing User: | Yovita Sari Cahyaningtyas | ||||||
| Date Deposited: | 24 Jun 2025 04:34 | ||||||
| Last Modified: | 24 Jun 2025 04:34 | ||||||
| URI: | https://sipora.polije.ac.id/id/eprint/42405 |
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