Corn Leaf Diseases Recognition Based on Convolutional Neural Network

Mutia Fadhilla
Suryani, Des
Labellapansa, Ause
Gunawan, Hendra

IT JOURNAL RESEARCH AND DEVELOPMENT
Vol. 8 No. 1 (2023)

Maize or known as corn is one of the most important agricultural commodities in Indonesia beside rice. Indonesia is located in a tropical area which has high rate of rainfall and humidity which makes it easy for fungi and bacteria that caused plant disease to thrive. It could be a threat which is a decrease of corn harvest due to plant diseases. To prevent this, a deep learning approach can be implemented to recognize plant diseases automatically based on visual pattern on leaves. In this study, we proposed a CNN-based model for corn leaf diseases recognition. Based on the results, the proposed method has great performance which accuracy score of 93%. Besides that, the proposed method achieved up to 100% precision and recall, and up to 99% F1 score.