Salsabila Oktafani, . (2024) IMPLEMENTASI METODE CONVOLUTIONAL NEURAL NETWORK TERHADAP KLASIFIKASI JENIS IKAN AIR TAWAR. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
The diversity of freshwater fish in Indonesia is one example of the wealth of Indonesia's aquatic resources. However, there are still shortcomings in the understanding of people who have not been able to distinguish the types of freshwater fish that exist. This can certainly cause the preservation of freshwater fish to be threatened if it continues to be left alone. There are many ways to attract people's attention in understanding the differences in freshwater fish species. For example, by applying the CNN model to several aquatic animal tourist attractions, especially freshwater fish, as a public education in identifying freshwater fish species efficiently as well as building educational attractions that attract visitors to increase knowledge on Indonesia's natural wealth. This research implements the CNN method of transfer learning, fine tuning ResNet-50 and VGG-16 which consists of 9 classes of freshwater fish species. The results showed that the highest accuracy value in the test was obtained when using fine tuning ResNet-50 with an accuracy value of 88.89% and a loss value of 0.56820.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2010511001] [Pembimbing 1: Nur Hafifah Matondang] [Pembimbing 2: Nindy Irzavika] [Penguji 1: Ridwan Raafi'udin] [Penguji 2: Muhammad Adrezo] |
| Uncontrolled Keywords: | Freshwater Fish, CNN, ResNet-50, VGG-16 |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | SALSABILA OKTAFANI |
| Date Deposited: | 30 Jul 2024 08:45 |
| Last Modified: | 28 Aug 2024 07:55 |
| URI: | http://repository.upnvj.ac.id/id/eprint/31536 |
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