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

Full Text:

PDF

References


Cong, P. et al. (2023) ‘MYOLO: A Lightweight Fresh Shiitake Mushroom Detection Model Based on YOLOv3’, Agriculture (Switzerland), 13(2). Available at: https://doi.org/10.3390/agriculture13020392.

Fadlil, A. (2012) ‘Sistem Pengenalan Citra Jenis-Jenis Tekstil’, Spektrum Industri: Jurnal Ilmiah Pengetahuan dan Penerapan Teknik Industri, 10(1), pp. 19–29. Available at: https://doi.org/10.12928/si.v10i1.1617.

Gustina, S., Fadlil, A. and Umar, R. (2017) ‘Sistem Identifikasi Jamur Menggunakan Metode Ekstraksi Ciri Statistik Orde 1 dan Klasifikasi Jarak’, Techno.Com, 16(4), pp. 378–386. Available at: https://doi.org/10.33633/tc.v16i4.1490.

Lee, C.-H. (2020) DEVELOPMENT OF A MUSHROOM HARVESTING ASSISTANCE SYSTEM USING COMPUTER VISION.

Mark S. Nixion; Alberto S. Aguado (2002) Feature Extraction and Image Processing.

Nurhayati, O.D. and Windasari, I.P. (2016) ‘Stroke identification system on the mobile based CT scan image’, ICITACEE 2015 - 2nd International Conference on Information Technology, Computer, and Electrical Engineering: Green Technology Strengthening in Information Technology, Electrical and Computer Engineering Implementation, Proceedings, pp. 113–116. Available at: https://doi.org/10.1109/ICITACEE.2015.7437781.

Rani, U. (2022) MUSHROOM CLASSIFICATION: A COMPARISON OF CLASSIFICATION ALGORITHMS USING MACHINE LEARNING TECHNIQUES. Available at: www.jetir.org.

Rokach, L. and Maimon, O. (2014) DATA MINING WITH DECISION TREES, Series in Machine Perception and Artificial Intelligence. Available at: https://doi.org/10.1088/1751-8113/44/8/085201.

Visa Sofia, D. (2011) ‘Confusion Matrix-based Feature Selection Sofia Visa’, ConfusionMatrix-based Feature Selection, 710(January), p. 8.




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

Article Metrics

Abstract view : 365 times
PDF - 324 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Cucut Hariz Pratomo, Widyastuti Andriyani

JOURNAL OF INTELLIGENT SOFTWARE SYSTEMS

Published by

Magister Teknologi Informasi
Lembaga Penelitian dan Pengabdian Masyarakat
Universitas Teknologi Digital Indonesia (d.h STMIK AKAKOM)
Jl. Raya Janti Jl. Majapahit No.143, Jaranan, Banguntapan,
Kec. Banguntapan, Kabupaten Bantul,
Daerah Istimewa Yogyakarta 55918

Website : https://www.utdi.ac.id/

 

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.