Amalia Hasanah, . (2024) IMPLEMENTASI METODE CONVOLUTIONAL NEURAL NETWORK UNTUK DETEKSI KEMATANGAN BUAH APEL MALANG. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Apples are a fruit that comes from subtropical areas and belongs to the Rosaceae family. Apples are also a popular fruit and have various types. The type of apple can be seen from the physical appearance of the fruit itself, namely from the skin and shape of the apple. It is actually possible to see the ripeness of Malang apples using the human eye, but it is not optimal. Apart from that, using artificial intelligence in this case will speed up the work of farmers. The author uses the CNN (Convolutional Neural Network) method to create this system, because basically CNN is an artificial condition network architecture used for image detection. In this research, the author used a method of comparing data before augmentation and after augmentation. The best research results were in experimental data after augmentation, with 99% accuracy.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2010511098 ] [Pembimbing 1 : Indra Permana Solihin ] [Pembimbing 2 : Nindy Irzavika ] [Penguji 1: Bayu Hananto ] [Penguji 2: Nurul Afifah Arifuddin ] |
| Uncontrolled Keywords: | Apple, Classification, CNN, Fruit Maturity, Image |
| 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: | AMALIA HASANAH |
| Date Deposited: | 05 Sep 2024 06:20 |
| Last Modified: | 05 Sep 2024 06:20 |
| URI: | http://repository.upnvj.ac.id/id/eprint/31312 |
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