Mushroom Image Classification Using C4.5 Algorithm

Cucut Hariz Pratomo, Widyastuti Andriyani

Abstract


This study applied five types of Mushrooms, they are Button mushrooms, Wood Ear mushrooms, Straw mushrooms, Reishi mushrooms and Red Oyster mushrooms. The feature extraction used is Order 1 with the parameters of mean, skewness, variance, kurtosis, and entropy. The process carried out to identify mushroom images by preparing image objects. There were 15 images of each mushroom class were taken for each mushroom and stored in .jpg format. The image processing is carried out by a feature extraction process. Then five images for each mushroom class are chosen. They were used as test images which will be classified so that identification results are obtained. This study applies the Classification Algorithm C4.5 to build a decision tree, which will also identify the results of the accuracy of processed mushroom images. The obtained result of accuracy was 84% in the classification of feature extraction Order 1

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References


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DOI: http://dx.doi.org/10.26798/jiss.v2i1.930

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Copyright (c) 2023 Cucut Hariz Pratomo, Widyastuti Andriyani

JOURNAL OF INTELLIGENT SOFTWARE SYSTEMS

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Lembaga Penelitian dan Pengabdian Masyarakat
Universitas Teknologi Digital Indonesia (d.h STMIK AKAKOM)
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