JAIS (Journal of Applied Intelligent System)
Vol 4, No 2 (2019): Journal of Applied Intelligent System

Rabbit Type Classification Using Multi-SVM Based on Feature Extraction

Ery Mintorini (STMIK KADIRI)
Wildan Mahmud (STMIK KADIRI)



Article Info

Publish Date
06 Mar 2020

Abstract

Rabbits reputation of being cute, fluffy, cuddly critters lend then to being a popular choice for children pets. But in raising a rabbit is not easy, this depends on the type of rabbit. Rabbits that commonly pet are Rex Rabbits, American Rabbits, and Giant Rabbits. Rex Rabbits itself has some species including Rex Amber and Rex Lilac species, Giant Rabbits rabbits includes Giant Chekered rabbit, Harleyquin, dan American White Rabbit. Classification technology can be used to help the classification process of rabbits are Multi-SVM method and image feature extraction to classify rabbit species. Feature extraction used in this study is mean, variance, skewness, kurtosis, entropy. The five features are classified with Multi-SVM. The data used in this study are 125 images, consisting of 100 training images and 25 test images. The accuracy of this method reached 92%. Keywords – Classification, Multi-SVM, Rabbit, Feature Extraction

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Journal Info

Abbrev

JAIS

Publisher

Subject

Description

Journal of Applied Intelligent System (JAIS) is published by LPPM Universitas Dian Nuswantoro Semarang in collaboration with CORIS and IndoCEISS, that focuses on research in Intelligent System. Topics of interest include, but are not limited to: Biometric, image processing, computer vision, ...