Implementasi Artificial Neural Network Untuk Identifikasi Penyakit Pada Jagung (Zea mays L.)

Hermawan, Fatur (2020) Implementasi Artificial Neural Network Untuk Identifikasi Penyakit Pada Jagung (Zea mays L.). Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

Corn (Zea mays L.), is one of the most important agricultural commodity crops for Indonesia, apart from wheat and rice. Local residents in Indonesia use maize as a staple food. Fluctuations in the production of maize. One of them is a disease that occurs in corn such as bulai, leaf spot, leaf rust, and leaf blight. To find out the types of diseases that often occur, an application that can identify the disease is needed, the program or application uses Digital Image Processing and Artificial Neural Networks using the Gray Level Co-Occurrence Matrix and Learning Vector Quantization methods. The accuracy of using this method is 64.4444%.

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