Classification of Diseases of Banana plant Fusarium Wilted Banana Leaf Using Support Vector Machine

Yus Rama Denny, Endi Permata, Lusiani Dewi Assaat

Abstract


Fusarium wilt is an important disease of various types of bananas and one of the most common diseases that causes destruction of banana plants in tropical and subtropical regions. Fusarium wilt caused by the fungus Fusarium oxysporum f.sp. cubense (FOC). As an inhabitant, invader, soil-transmitted fungus and causes wilt that colonizes xylem vessels, FOC requires penetration through the roots of the host plant, so that in its control it is necessary to try to provide protection and induction of host resistance systems in the root system. in this research.

The proposed banana plant disease detection system consists of two phases, in the first phase, namely in the learning process, the images of healthy banana leaves and those affected by fusarium disease are files each measuring 640x480 pixels obtained from the results of taking a digital microscope on the plantation. PT. GGP Lampung. Next is the classification process. The method used for pattern recognition in this study is a support vector machine (SVM). Basically SVM can only be used to classify data into two classes (binary classification). To be able to apply to the problem of classifying healthy banana leaves and those affected by mild, moderate and severe fusarium disease consisting of more than two classes, a multiclass SVM classification method is applied which is built by combining several binary classifications. In the training classification process, the hyperplane variables for each classifier obtained will be stored and will later be used as data for each classifier in the testing process, in other words the training classification process is a process to find support vectors, alpha and bias from the training input data obtained. in the form of a feature vector from the image of healthy banana leaves and those with mild, moderate and severe fusarium disease (four classes). From the results of the classification stage experiment using the support vector machine one against all method, the results obtained are Class I (Healthy Banana Leaf) 90.833%, Class II (Light Fusarium Banana Leaf) 76.688%, Class III (Medium Fusarium Banana Leaf) 77.50, Class III (Medium Fusarium Banana Leaf) IV(Fusarium banana leaf weight) 95%.


Keywords


fusarium wilted, Banana Leaf, Support vector Machine, feature extraction, image processing

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DOI: http://dx.doi.org/10.30870/gravity.v8i1.15893

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