Transfer Learning Approach for Eye Disease Classification Using Images with CNN InceptionV3
DOI:
https://doi.org/10.37859/coscitech.v6i1.8509
Keywords:
Eye disease classification, InceptionV3, Transfer Learning Klasifikasi penyakit mata, InceptionV3, Transfer Learning
Abstract
Eye diseases are a leading cause of vision impairment and blindness worldwide. Therefore, detection of eye diseases is crucial in the prevention of blindness. This study develops an eye disease classification model based on Convolutional Neural Network (CNN) using Transfer Learning with InceptionV3. The dataset consists of 1559 images, divided into 1249 training images and 310 validation images, covering 8 eye disease classes. The model was trained using 40 epochs with the Adam optimizer. Evaluation results show a validation accuracy of 81.29%. While the model performed well, some classes, such as hordeolum, showed lower accuracy, indicating areas that need further improvement. This study confirms that Transfer Learning with InceptionV3 is an effective approach for eye disease classification.
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F. N. Cahya, N. Hardi, D. Riana, and S. Hadiyanti, “Klasifikasi penyakit mata menggunakan convolutional neural network (CNN),” Sistemasi, vol. 10, no. 3, p. 618, Sep. 2021, doi: 10.32520/stmsi.v10i3.1248.
D. Marcella, Y. Yohannes, and S. Devella, “Klasifikasi penyakit mata menggunakan convolutional neural network dengan arsitektur VGG-19,” Jurnal Algoritme, vol. 3, no. 1, pp. 60–70, Oct. 2022, doi: 10.35957/algoritme.v3i1.3331.
Mukhlis Santoso, Sarjon Defit, and Yuhandri, “Penerapan Convolutional Neural Network pada Klasifikasi Citra Pola Kain Tenun Melayu,” Jurnal CoSciTech (Computer Science and Information Technology), vol. 5, no. 1, pp. 177–184, May 2024, doi: 10.37859/coscitech.v5i1.6713
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Mohammad Haydir Awaludin Waskito, Andreas Nugroho Sihananto, and Achmad Junaidi, “Klasifikasi Penyakit Kronis Melalui Mata Menggunakan Algoritma Convolutional Neural Network Dengan Model MobileNet-V3,” Uranus : Jurnal Ilmiah Teknik Elektro, Sains dan Informatika, vol. 2, no. 2, pp. 48–60, Jun. 2024, doi: 10.61132/uranus.v2i2.120.
S. Satria, Sumijan, and Billy Hendrik, “Implementasi Convolutional Neural Netowork Untuk Klasifikasi Citra KTP-El,” Jurnal CoSciTech (Computer Science and Information Technology), vol. 5, no. 1, pp. 169–176, May 2024, doi: 10.37859/coscitech.v5i1.6708.
C. and M. Methods in Medicine, “Retracted: Cataract Disease Detection by Using Transfer Learning‐Based Intelligent Methods,” Computational and Mathematical Methods in Medicine, vol. 2023, no. 1, Jan. 2023, doi: 10.1155/2023/9837079.
Dataset 8 Class Penyakit Mata, https://bit.ly/EyeDiseaseDataset.
M. Iksan Maulana, M. Martanto, and U. Hayati, “Perbandingan Algoritma Naïve Bayes Dan K-Nearest Neighbors Untuk Klasifikasi Topik Berita Pada Situs Detik.Com,” JATI (Jurnal Mhs. Tek. Inform., vol. 8, no. 3, pp. 3733–3742, 2024, doi: 10.36040/jati.v8i3.9779.
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A. Herbert, P. Sitohang, T. I. Hermanto, and C. D. Lestari, “Tumbuhan Stroberi Menggunakan Metode Convolutional Neural Network Arsitektur,” JITET (Jurnal Informatika dan Teknik Elektro Terapan), vol. 12, no. 3, 2024, [Online]. Available: https://journal.eng.unila.ac.id/index.php/jitet/article/view/5274/2160.
A. W. Kosman, Y. Wahyuningsih, and F. Mahendrasusila, “Pengujian Metode Inception V3 dalam Mengidentifikasi Penyakit Kanker Kulit,” Jurnal Teknologi Informasi dan Komputer, vol. 10, no. 1, pp. 132–142, 2024, doi: 10.37012/jtik.v10i1.1940.
D. Martomanggolo, “Perbandingan Convolutional Neural Network pada Transfer Learning Method untuk Mengklasifikasikan Sel Darah Putih,” Ultimatics: Jurnal Teknik Informatika, vol. 13, no. 1, p. 51, 2021, [Online]. Available: https://ejournals.umn.ac.id/index.php/TI/article/view/2040/1107
M. Iksan Maulana, M. Martanto, and U. Hayati, “Perbandingan Algoritma Naïve Bayes Dan K-Nearest Neighbors Untuk Klasifikasi Topik Berita Pada Situs Detik.Com,” JATI (Jurnal Mahasiswa. Teknik Informatika., vol. 8, no. 3, pp. 3733–3742, 2024, doi: 10.36040/jati.v8i3.9779.
F. Mustakim, F. Fauziah, and N. Hayati, “Algoritma Artificial Neural Network pada Text-based Chatbot Frequently Asked Question (FAQ) Web Kuliah Universitas Nasional,” J. JTIK (Jurnal Teknologi Informasi dan Komunikasi), vol. 5, no. 4, p. 438, 2021, doi: 10.35870/jtik.v5i4.261.
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Published
2025-05-27
How to Cite
Gunawan, R. ., Fathurrahman, R., Widyaningrum, A. I. S., Issandra, F. ., Abdurachman, M. A., Putra, Y. E., & Naufal. (2025). Transfer Learning Approach for Eye Disease Classification Using Images with CNN InceptionV3. Jurnal CoSciTech (Computer Science and Information Technology), 6(1), 60–67. https://doi.org/10.37859/coscitech.v6i1.8509
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