The Implementation of Jaro-Winkler Distance and Naive Bayes Classifier for Identification System of Pests and Diseases on Paddy
Abstract
The identification of pests and diseases on paddy are required to determine the control that can be done. Control of pests and diseases of paddy that are less precise as the excessive and prolonged use of pesticides can cause harm to the rice plant itself. This research aims to create a system to identify pests and diseases of paddy as well as provide alternative solutions to control it. This research proposes Jaro-Winkler Distance and Naive Bayes Classifier in identifying pests and diseases of paddy. The system takes text that contains symptoms of the disease as an input. The identification system in this research utilizes Jaro-Winkler Distance to identify symptoms from user input and Naive Bayes Classifier to identify what kind of pest or disease that infected the paddy. Developed applications got 93% accuracy, 94% precision, and 92% recall on evaluation using 10-fold cross-validation.
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