KLASIFIKASI HAMA DAN PENYAKIT PADA TANAMAN JAGUNG BERDASARKAN NILAI RATA-RATA CITRA RED GREEN BLUE (RGB) DENGAN METODE NAIVE BAYES DAN K-NEAREST NEIGHBOR

PUTRI, MEGA TIARA and Resti, Yulia (2021) KLASIFIKASI HAMA DAN PENYAKIT PADA TANAMAN JAGUNG BERDASARKAN NILAI RATA-RATA CITRA RED GREEN BLUE (RGB) DENGAN METODE NAIVE BAYES DAN K-NEAREST NEIGHBOR. Undergraduate thesis, Sriwijaya University.

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Abstract

Corn (Zeamays L) is one of the most important carbohydrate-producing foodstuffs in the world besides wheat and rice. Corn plants are sensitive to pests and diseases which can result in a decrease in the quantity and quality of the production. Eradicate pests and diseases according to their type is a solution to overcome the problem of disease in corn plants. The purpose of the research to classify pests and diseases on corn plants based on the average value of the Red Green Blue (RGB) image using the Naïve Bayes and K-Nearest Neighbor methods. The data used consisted of 761 photo samples with 6 classifications of pests and diseases on corn plants. The results of this study are the Naïve Bayes method can classify pests and diseases of corn plants with an accuracy level of 85.52%, precision of 56.57%, and recall of 56.57%. The K-Nearest Neighbor method can classify corn plant pests and diseases with an accuracy level of 92.54%, precision of 77.63%, and recall of 77.63%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Corn, RGB Image, Naïve Bayes Method, K-Nearest Neighbor Method
Subjects:	Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics > QA279.C663 Response surfaces (Statistics)
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	MEGA TIARA PUTRI
Date Deposited:	28 Sep 2021 02:32
Last Modified:	28 Sep 2021 02:32
URI:	http://repository.unsri.ac.id/id/eprint/55007

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