Klasifikasi Kesegaran Daging Sapi Menggunakan Deep Learning Arsitektur VGG16 Dengan Augmentasi Citra
Abstract
Beef is one of the best foods to eat. However, to identify beef manually has a weakness, namely the limitations of human visual abilities. Therefore it is necessary to have an indicator of the level of freshness of the meat. This study uses image augmentation to change or modify images and use Convolutional Neural Network (CNN) with VGG16 architecture to perform image classification. The accuracy obtained with epoch 15 and the distribution of data by 80% of training data and 20% of validation data is the highest accuracy obtained, which is 97.14% and when tested with validation data it gets an accuracy of 98.68%. Overall, the model that has been used can classify the freshness of beef well.
References
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[16] D. Albashish , R. Al-Sayyed , A. Abdullah, M. H. Ryalat and N. A. Almansour, "Deep CNN Model based on VGG16 for Breast Cancer Classification," 2021 International Conference on Information Technology (ICIT), pp. 805-810, 2021.
[2] T. Yulianti, M. Telaumbanua, H. D. Septama, H. Fitriawan and A. Yudamson, "PENGARUH SELEKSI FITUR CITRA TERHADAP KLASIFIKASI TINGKAT," Jurnal Teknik Pertanian Lampung, vol. 10, no. 1, pp. 85-95, 2021.
[3] I. M. Perez de Vargas-Sansalvador, M. M. Erenas, A. Martínez-Olmos, F. Mirza-Montoro, L. F. Capitan-Vallvey and D. Diamond, "Smartphone based meat freshness detection," Talanta, vol. 216, pp. 1-6, 2020.
[4] A. Herdiansah, R. I. Borman, D. Nurnaningsih, A. A. J. Sinlae and R. R. Al Hakim, "Klasifikasi Citra Daun Herbal Dengan Menggunakan Backpropagation Neural Networks Berdasarkan Ekstraksi Ciri Bentuk," JURIKOM (Jurnal Riset Komputer), vol. 9, no. 2, pp. 388-395, 2022.
[5] H. M. Al-Jabbar, H. Fitriyah and R. Maulana, "Sistem Klasifikasi Kesegaran Daging Sapi berdasarkan Citra menggunakan Metode Naïve Bayes berbasis Raspberry Pi," Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 5, no. 4, pp. 1646-1653, 2021.
[6] S. F. Astari, I. G. P. S. Wijaya and I. B. K. Widiartha, "Klasifikasi Jenis dan Tingkat Kesegaran Daging Berdasarkan Warna, Tekstur dan Invariant Moment Menggunakan Klasifikasi LDA," J-COSINE, vol. 5, no. 1, pp. 9-19, 2021.
[7] Radikto, D. I. Mulyana, M. A. Rofik and M. O. Z. Zakaria, "Klasifikasi Kendaraan pada Jalan Raya menggunakan Algoritma Convolutional Neural Network ( CNN )," Jurnal Pendidikan Tambusai, vol. 6, no. 1, pp. 1668-1679, 2022.
[8] O. Ulucan, D. Karakaya and M. Turkan, "Meat Quality Assessment based on Deep Learning," 2019 Innovations in Intelligent Systems and Applications Conference (ASYU), pp. 1-5, 2019.
[9] K. H. Mahmud, Adiwijaya and S. Al Faraby, "Klasifikasi Citra Multi-Kelas Menggunakan Convolutional Neural Network," e-Proceeding of Engineering, vol. 6, no. 1, pp. 2127-2136, 2019.
[10] L. Nanni, M. Paci, S. Brahnam and A. Lumini, "Comparison of Different Image Data Augmentation Approaches," Journal of Imaging, vol. 7, no. 12, p. 254, 2021.
[11] A. Putri, B. S. Negara and S. Sanjaya, "Penerapan Deep Learning Menggunakan VGG-16 untuk Klasifikasi Citra Glioma.," PENERAPAN DEEP LEARNING MENGGUNAKAN VGG-16 UNTUK KLASIFIKASI CITRA GLIOMA, vol. 3, no. 4, pp. 379-383, 2022.
[12] M. F. Naufal, S. Huda, A. Budilaksono, W. A. Yustisia, A. A. Arius, F. A. Miranti and F. A. T. Prayoga, "Klasifikasi Citra Game Batu Kertas Gunting Menggunakan Convolutional Neural Network," Techno.COM, vol. 20, no. 1, pp. 166-174, 2021.
[13] A. Mulyanto, E. Susanti, F. Rossi, Wajiran and R. I. Borman, "Penerapan Convolutional Neural Network (CNN) pada Pengenalan Aksara Lampung Berbasis Optical Character Recognition (OCR)," JEPIN (Jurnal Edukasi dan Penelitian Informatika), vol. 7, no. 1, pp. 52-57, 2021.
[14] S. Kumaresan, K. S. Aultrin, S. S. Kumar and M. D. Anand, "Transfer Learning with CNN for Classification of Weld Defect," IEEE Access, vol. 9, pp. 95097-95108, 2021.
[15] E. Tanuwijaya and A. Roseanne, "Modifikasi Arsitektur VGG16 untuk Klasifikasi Citra Digital Rempah-Rempah Indonesia," Matrik: Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer, vol. 21, no. 1, 2021.
[16] D. Albashish , R. Al-Sayyed , A. Abdullah, M. H. Ryalat and N. A. Almansour, "Deep CNN Model based on VGG16 for Breast Cancer Classification," 2021 International Conference on Information Technology (ICIT), pp. 805-810, 2021.
Published
2022-11-25
How to Cite
ELIA, Benny; DARMAWAN, I Dewa Made Bayu Atmaja.
Klasifikasi Kesegaran Daging Sapi Menggunakan Deep Learning Arsitektur VGG16 Dengan Augmentasi Citra.
Jurnal Nasional Teknologi Informasi dan Aplikasnya, [S.l.], v. 1, n. 1, p. 317-324, nov. 2022.
ISSN 3032-1948.
Available at: <https://ojs.unud.ac.id/index.php/jnatia/article/view/92586>. Date accessed: 10 jan. 2025.
Section
Articles
