SETIAWAN, MICHAEL JEFFRY (2023) KLASIFIKASI PENYAKIT DAUN TANAMAN BUAH DAN SAYUR MENGGUNAKAN ALGORITMA CNN DAN RANDOM FOREST. Undergraduate thesis, UNIVERSITAS PEMBANGUNAN NASIONAL VETERAN JAWA TIMUR.
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Abstract
Leaf disease is a disease that occurs on leaves and is caused by fungi or bacteria that are spread through soil, air or water. In general, the classification of leaf diseases is carried out using the traditional method by observing changes in the leaf surface. This method has disadvantages when compared to classification methods using machine learning or deep learning technology such as CNN, Fandom Forest, XGBoost or other classification methods. In this study, a classification process was carried out using the random forest algorithm based on data obtained from CNN feature extraction, the research process was carried out with the stages of data collection, data sorting, data labeling, making the CNN model, CNN feature extraction, making the Random Forest model, to testing the program based on the Random Forest model that has been obtained to determine the level of effectiveness of this algorithm method in classifying leaf diseases on fruit and vegetable plants.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | T Technology > T Technology (General) | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | Michael Jeffry Setiawan | ||||||||||||
| Date Deposited: | 24 Jul 2023 06:54 | ||||||||||||
| Last Modified: | 24 Jul 2023 06:54 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/16150 |
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