IDENTIFICATION OF HERBAL LEAF TYPES BASED ON THEIR IMAGE USING FIRST ORDER FEATURE EXTRACTION AND MULTICLASS SVM ALGORITHM

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UEU » Proceeding » Teknik Informatika
Posted by [email protected] at 18/02/2022 20:57:59 • 495 Views

IDENTIFICATION OF HERBAL LEAF TYPES BASED ON THEIR IMAGE USING FIRST ORDER FEATURE EXTRACTION AND MULTICLASS SVM ALGORITHM

Created by :
Rohmat Indra Borman ( none )
Farli Rossi ; Yessi Jusman ; Ashrani Aizzuddin Abd. Rahni ; Syahrizal Dwi Putra (0307057504) ; Arief Herdiansah

Subject:	PANDEMI COVID-19 IMUNITAS
Alt. Subject :	IMAGE IDENTIFICATION MULTICLASS SVM
Keyword:	KONSUMSI HERBAL KESEHATAN

Alt. Description

One way to increase immunity and maintain immunity can be done by consuming herbal plants. This herbal medicine is empirically believed to be useful as a cultural treasure from generation to generation. All parts of the plant can be used as medicine, one of which is the leaves. However, most people do not know the herbal leaves. This herbal leaf can actually be recognized from the characteristics of its shape. This study aims to identify types of herbal leaves using first-order feature extraction and the Multiclass Support Vector Machine (Multiclass SVM) algorithm. First-order feature extraction is able to extract features using the parameters of mean, skewness, variance, kurtosis, and entropy. Meanwhile, Multiclass SVM identifies by obtaining the optimal line in separating the data set of two classes of two-dimensional space points in order to find the maximum hyperplane in separating the data points into classes so that they can be grouped. From the test results, the identification accuracy is an average of 76%. This shows that the algorithm has been able to identify, but needs improvement.

Date Create	:	18/02/2022
Type	:	Text
Format	:	pdf
Language	:	Indonesian
Identifier	:	UEU-Proceeding-14_0245
Collection ID	:	14_0245

Source :
2021 1st International Conference on Electronic and Electrical Engineering and Intelligent System (ICE3IS)

Relation Collection:
Fakultas Ilmu Komputer

Coverage :
Civitas Akademika Universitas Esa Unggul

Rights :
@2022 Perpustakaan Universitas Esa Unggul

Publication URL :
https://digilib.esaunggul.ac.id/identification-of-herbal-leaf-types-based-on-their-image-using-first-order-feature-extraction-and-multiclass-svm-algorithm-23554.html

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