Alysha Zahira Farras Ihsani, . (2024) IMPLEMENTASI ALGORITMA CONVOLUTIONAL NEURAL NETWORK (CNN) UNTUK KLASIFIKASI CITRA REMPAH RIMPANG BERBASIS GUI. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
As time passed, people tended to use instant spices more often that were considered more efficient to use than original spice blends. Apart from that, the many different types of rhizomes with similar shapes and colors make it difficult for some people to differentiate one type of spice from another. Therefore, this research creates a Convolutional Neural Network (CNN) model which can make it easier for people to recognize rhizome spices. CNNs are designed to resemble connections between neurons such as neurons in the human brain which have a major role in receiving and processing visual stimuli. Therefore, CNNs are very useful in tasks for image recognition and classification. In this research, the second experiment was the best model in classifying 6 types of rhizome spices with an accuracy value of 97%, precision of 97%, recall of 97%, and F1-Score of 97%.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2010511118] [Pembimbing 1: Indra Permana Solihin] [Pembimbing 2: Hamonangan Kinantan Prabu] [Penguji 1: Iin Ernawati] [Penguji 2: Ika Nurlaili Isnainiyah] |
| Uncontrolled Keywords: | CNN, Classification, Rhizome Spices |
| 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: | ALYSHA ZAHIRA FARRAS IHSANI |
| Date Deposited: | 29 Jul 2024 14:05 |
| Last Modified: | 29 Jul 2024 14:05 |
| URI: | http://repository.upnvj.ac.id/id/eprint/31537 |
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