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PENGKLASIFIKASIAN HAMA DAN PENYAKIT TANAMAN JAGUNG MENGGUNAKAN METODE SUPPORT VECTOR MACHINE DAN K-NEAREST NEIGHBOR BERDASARKAN RESAMPLING REPEATED K-FOLD CROSS VALIDATION

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Cultivation of corn plants has obstacles such as being attacked by pests and diseases that cause crop yields to decline and harm farmers. Performance indicators are especially useful when the goal is to compare different classification models. This study aims to classify pests and diseases of corn using the Support Vector Machine and K-Nearest Neighbor methods based on Resampling Repeated K-Fold Cross Validation with red, green, and blue (RGB) images, so that farmers can easily maintain the stability of corn crop yields. The accuracy obtained from the classification of pests and diseases of corn plants based on Resampling Repeated K-Fold Cross Validation with red, green, and blue (RGB) images using the Support Vector Machine method is 85.39%, while using the K-Nearest Neighbor method is 84.65%.

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Detail Information

Series Title

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Call Number

T723622022

Publisher

Inderalaya : Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Sriwijaya., 2022

Collation

xvi, 486 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

516.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Jurusan Matematika
Ilmu Ukur, Geometri

Specific Detail Info

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Statement of Responsibility

SEPTA

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