KLASIFIKASI DAGING SAPI DAN DAGING BABI MENGGUNAKAN ARSITEKTUR EFFICIENTNET-B3 DAN AUGMENTASI DATA
Abstract
The increasing demand for beef has made its price soar. the traders then mix beef with pork to get more profit. There is a technology in the field of informatics that can be used to differentiate beef, pork and mixed meat. This research was conducted to find out the difference between beef, pork and mixed meat. In this study, a deep learning convolutional neural network with the EfficientNet-B3 architecture is used for image identification to distinguish between beef and pork. 9000 images have been divided into three categories: mixed meat, pork and beef. This study compares the classification results using original data and data augmentation. The data augmentation models used are brightness, rotation, and horizontal and vertical inversion. Data is split 80:20 and 90:10 for training and testing respectively. The best results are achieved by using a division ratio of 90:10 on image data with augmentation which has a learning rate of 0.01 and Adamax Optimizer which has accuracy, precision and recall levels of 98.66%, 98.67% and 98.66%.
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[11] S. Lasniari, J. Jasril, S. Sanjaya, F. Yanto, and M. Affandes, “Klasifikasi Citra Daging Babi dan Daging Sapi Menggunakan Deep Learning Arsitektur ResNet-50 dengan Augmentasi Citra,” J. Sist. Komput. dan Inform., vol. 3, no. 4, p. 450, 2022, doi: 10.30865/json.v3i4.4167.
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[13] H. Alhichri, A. S. Alswayed, Y. Bazi, N. Ammour, and N. A. Alajlan, “Classification of Remote Sensing Images Using EfficientNet-B3 CNN Model with Attention,” IEEE Access, vol. 9, pp. 14078–14094, 2021, doi: 10.1109/ACCESS.2021.3051085.
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[15] E. Anggiratih, S. Siswanti, S. K. Octaviani, and A. Sari, “Klasifikasi Penyakit Tanaman Padi Menggunakan Model Deep Learning Efficientnet B3 dengan Transfer Learning,” J. Ilm. SINUS, vol. 19, no. 1, p. 75, 2021, doi: 10.30646/sinus.v19i1.526.
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[17] S. R. Salian and S. D. Sawarkar, “Melanoma Skin Lesion C Lassification Using Improved Efficientnetb 3,” vol. 08, no. 01, pp. 45–57, 2022.
[18] H. Habibi Aghdam, E. Jahani Heravi, and S. I. P. AG, Guide to Convolutional Neural Networks A Practical Application to Traffic-Sign Detection and Classification. 2018. doi: 10.1007/978-3-319-57550-6.
Published
2023-06-30
How to Cite
JUNIHARDI, Maulana et al.
KLASIFIKASI DAGING SAPI DAN DAGING BABI MENGGUNAKAN ARSITEKTUR EFFICIENTNET-B3 DAN AUGMENTASI DATA.
Jurnal Tekinkom (Teknik Informasi dan Komputer), [S.l.], v. 6, n. 1, p. 16-25, june 2023.
ISSN 2621-3079.
Available at: <https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/view/845>. Date accessed: 20 may 2024.
doi: https://doi.org/10.37600/tekinkom.v6i1.845.
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