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

RIZQI, TASYA ANISAH and Resti, Yulia and Zayanti, Des Alwine (2022) PENGKLASIFIKASIAN HAMA DAN PENYAKIT TANAMAN JAGUNG MENGGUNAKAN METODE SUPPORT VECTOR MACHINE DAN K-NEAREST NEIGHBOR BERDASARKAN RESAMPLING REPEATED K-FOLD CROSS VALIDATION. Undergraduate thesis, Sriwijaya University.

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Abstract

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%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Tanaman Jagung, Support Vector Machine, K-Nearest Neighbor, Repeated K-Fold Cross Validation, Citra RGB
Subjects:	Q Science > QA Mathematics > QA8.9-QA10.3 Computer science. Artificial intelligence. Computational complexity. Data structures (Computer scienc. Mathematical Logic and Formal Languages
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Tasya Anisah Rizqi
Date Deposited:	15 Jun 2022 01:47
Last Modified:	15 Jun 2022 01:47
URI:	http://repository.unsri.ac.id/id/eprint/72362

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