IMPLEMENTASI MODEL DEEP LEARNING CONVOLUTIONAL NEURAL NETWORK (CNN) PADA CITRA PENYAKIT DAUN JAGUNG UNTUK KLASIFIKASI PENYAKIT TANAMAN
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Abstract
Corn is one of the main ingredients or staple besides rice. In agriculture’s world, leaf diseases appear that cause hampered and disturbed of corn plant growth. This research has a purpose to give a solution to detect whether the corn plant is diseased or not. Classification of leaf disease corn plants use a deep learning model Convolutional Neural Network (CNN). On this test, a numbered dataset is used: 3718 images for healthy corn leaf, and 3814 images for disease corn leaf in this case common rust. From this test result with data ratio 40% for data test, and 60% data train within training of 50 epochs obtained accuracy get a value of 0.9990, precision value get a value by 0.9981, recall get a value by 1, and F1 score get a value by 0,9990
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