DETECTION OF DISEASE ON CORN PLANTS USING CONVOLUTIONAL NEURAL NETWORK METHODS

Ardi Hidayat, Ucuk Darusalam, Irmawati Irmawati

Abstract


Deep Learning is still an interesting issue and is still widely studied. In this study Deep Learning was used for the diagnosis of corn plant disease using the Convolutional Neural Network (CNN) method, with a total dataset of 3.854 images of diseases in corn plants, which consisted of three types of corn diseases namely Common Rust, Gray Leaf Spot, and Northern Leaf Blight. With an accuracy of 99%, in detecting disease in corn plants.

Keywords


Convolutional Neural Network, Corn Plants, Deep Learning.

Full Text:

PDF


DOI: http://dx.doi.org/10.21609/jiki.v12i1.695

Refbacks



Copyright © Jurnal Ilmu Komputer dan Informasi. Faculty of Computer Science Universitas Indonesia.

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

View JIKI Statistic