ELINVO (Electronics, Informatics, and Vocational Education)
Vol 8, No 1 (2023): Mei 2023

Comparison of Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), and Stochastic Gradient Descent (SGD) for Classifying Corn Leaf Disease based on Histogram of Oriented Gradients (HOG) Feature Extraction

Firdaus Solihin (Departemen of Informatics, Faculty of Engineering, University of Trunojoyo, Madura, Bangkalan, Indonesia)
Muhammad Syarief (Departemen of Informatics, Faculty of Engineering, University of Trunojoyo, Madura, Bangkalan, Indonesia)
Eka Mala Sari Rochman (Departemen of Informatics, Faculty of Engineering, University of Trunojoyo, Madura, Bangkalan, Indonesia)
Aeri Rachmad (Departemen of Informatics, Faculty of Engineering, University of Trunojoyo, Madura, Bangkalan, Indonesia)

Article Info

Publish Date
19 Jun 2023

Abstract

Image classification involves categorizing an image's pixels into specific classes based on their unique characteristics. It has diverse applications in everyday life. One such application is the classification of diseases on corn leaves. Corn is a widely consumed staple food in Indonesia, and healthy corn plants are crucial for meeting market demands. Currently, disease identification in corn plants relies on manual checks, which are time-consuming and less effective. This research aims to automate disease identification on corn leaves using the Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) with K=2, and Stochastic Gradient Descent (SGD) algorithms. The classification process utilizes the Histogram of Oriented Gradients (HOG) feature extraction method with a dataset of corn leaf images. The classification results achieved an accuracy of 71.44%, AUC of 79.16%, precision of 70.08%, recall of 71.44%, and f1 score of 67.11%. The highest accuracy was obtained by combining HOG feature extraction with the SGD algorithm.

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Journal Info
ELINVO (Electronics, Informatics, and Vocational Education)
Website

Abbrev

elinvo

Publisher

Universitas Negeri Yogyakarta

Subject

Computer Science & IT Education Electrical & Electronics Engineering

Description

ELINVO (Electronics, Informatics and Vocational Education) is a peer-reviewed journal that publishes high-quality scientific articles in Indonesian language or English in the form of research results (the main priority) and or review studies in the field of electronics and informatics both in terms ...