IDENTIFIKASI PENYAKIT PADA DAUN JERUK SIAM (Citrus Nobilis Lour. Var. Microcarpa) BERDASARKAN GRAY LEVEL CO-OCCURRENCE MATRIX

Letishya Ramona, Shenila (2023) IDENTIFIKASI PENYAKIT PADA DAUN JERUK SIAM (Citrus Nobilis Lour. Var. Microcarpa) BERDASARKAN GRAY LEVEL CO-OCCURRENCE MATRIX. Other thesis, Politeknik Negeri Jember.

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Abstract

In Indonesia, orange production faces annual fluctuations primarily due to diseases caused by viruses, bacteria, and pests. These diseases manifest visible symptoms on the leaves, allowing for the identification of specific types such as leaf cancer and citrus leaf miner. However, manual disease checking methods lack accuracy in determining the precise type of disease affecting orange plants. This research aims to assist orange farmers in distinguishing between leaf cancer and citrus leaf miner diseases. It utilizes Artificial Neural Network with green-blue color feature parameters obtained from RGB image color decomposition. Texture feature extraction is performed using the Gray Level Co-occurrence Matrix (GLCM) method, considering features like Angular Second Moment (ASM), Contrast, Inverse Difference Moment (IDM), and Correlation. The study incorporates 225 data points divided into 180 training and 45 test samples. The Artificial Neural Network method achieves accuracies of 82.22% for training data and 80% for test data.

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