Skripsi

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

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Penilaian

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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%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107003414	T55007	T550072021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T550072021

Publisher

Indralaya : Prodi Ilmu Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam., 2021

Collation

xv, 69 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

519.707

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Prodi Ilmu Matematika
Matematika Pemrograman
Metode Naive Bayes

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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