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All Journal Jurnal Simetris Kompak : Jurnal Ilmiah Komputerisasi Akuntansi E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Pixel : Jurnal Ilmiah Komputer Grafis Elkom: Jurnal Elektronika dan Komputer JOURNAL OF APPLIED INFORMATICS AND COMPUTING Krea-TIF: Jurnal Teknik Informatika EDUMATIC: Jurnal Pendidikan Informatika EVOLUSI : Jurnal Sains dan Manajemen JSAI (Journal Scientific and Applied Informatics) Building of Informatics, Technology and Science Jurnal Komunitas: Jurnal Pengabidian Kepada Masyarakat Indonesian Journal of Electrical Engineering and Computer Science Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknologi Informasi dan Komunikasi Advance Sustainable Science, Engineering and Technology (ASSET) Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Journal of Engineering, Electrical and Informatics (JEEI) Dinamika Jurnal Publikasi Ilmu Komputer dan Multimedia Jurnal Teknik Informatika dan Teknologi Informasi JURNAL AKUNTANSI DAN BISNIS Community: Jurnal Pengabdian Pada Masyarakat Journal of Technology Informatics and Engineering Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian Scientific Journal of Informatics Switch: Jurnal Sains dan Teknologi Informasi Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Pelayanan Unggulan: Jurnal Pengabdian Masyarakat Terapan Inovasi Sosial: Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika dan Teknologi Informasi
Sindhu Rakasiwi
Universitas Sains Dan Teknologi Komputer
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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Journal : Scientific Journal of Informatics

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Deep Learning-Based Eye Disorder Classification: A K-Fold Evaluation of EfficientNetB and VGG16 Models Paramita, Cinantya; Rakasiwi, Sindhu; Andono, Pulung Nurtantio; Shidik, Guruh Fajar; Shier Nee Saw; Rafsanjani, Muhammad Ivan
Scientific Journal of Informatics Vol. 12 No. 3: August 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i3.26257

Abstract

Purpose: The study evaluates EfficientNetB3 and VGG16 deep learning architectures for image classification, focusing on stability, accuracy, and interpretability. It uses Gradient-weighted Class Activation Mapping to improve transparency and robustness. The research aims to create reliable AI-based diagnostic tools. Methods: The study used a dataset of 4,217 color retinal fundus images divided into four classes: cataract, diabetic retinopathy, glaucoma, and normal. The dataset was divided into 70% for training, 10% for validation, and 20% for testing. The researchers used a transfer learning approach with EfficientNetB3 and VGG16 models, pretrained on ImageNet. Real-time augmentation was applied to prevent overfitting and improve generalization. The models were compiled with the Adam optimizer and trained with categorical cross-entropy loss. Early stopping was implemented to allocate computational resources efficiently and reduce overfitting. A learning rate scheduler (ReduceLROnPlateau) was added to adjust the learning rate if no significant improvement was made concerning validation loss. EfficientNetB3 was more efficient in model size, possessing only 12 million parameters compared to VGG16's 138 million, making it suitable for resource-constrained mobile or embedded systems. The final evaluation was done on the held-out test set. Result: The EfficientNetB3 architecture outperforms VGG16 in classification accuracy and loss value stability, with an average accuracy of 93%. It also exhibits better transparency and predicted accuracy, making it a reliable model for medical image categorization. Novelty: This work introduces a novel framework integrating EfficientNetB3 architecture, stratified cross-valuation, L2 regularization, and Grad-CAM-based interpretability, focusing on openness and explainability in model evaluation.
Co-Authors Abu Salam Adhesyah Putra, Maulana Damar Agus Cahyo Pangestu Agustinus Budi Santoso Albastomi, Taqius Shofi Andi Dharu Permana Andriana, Myra Arifin, Muhammad Farhan Ariyanto, Noval Arya Erlangga Astuti, Yani Parti budi hartono Cahaya Jatmiko Cahaya Jatmoko Cahyo Pangestu , Agus Candra Irawan Catur Supriyanto Daurat Sinaga Deddy Award Widya Laksana Dewi Agustini Santoso Dzaky, Azmi Abiyyu Edi Sugiarto Edwin Zusrony Edy Mulyanto Egia Rosi Subhiyakto Egia Rosi Subhiyakto, Egia Rosi Erlin Dolphina Erna Zuni Astuti Erna Zuni Astuti Erwin Yudi Hidayat Etika Kartikadarma Febryantahanuji Febryantahanuji Feri Agustina Fikri Budiman Fitriyani, Shelomita Guruh Fajar Shidik Haresta, Alif Agsakli Haryo Kusumo Haryo Kusumo Haryo Kusumo Heribertus Himawan Heru Lestiawan Ifan Rizqa Ika Novita Dewi Indra Laila Intan Nurul Alfiani Isnaini Khusnul Khotimah Jarot Dian Susatyono Jarot Dian Susatyono Jatmiko, Cahaya Junta Zeniarja Khani, Nadia Ifti Kurniawan, Defri Kusumo , Haryo Kusumo, Haryo Lalang Erawan Lalang Erawan Lutfi Ubaidillah Marjuni, Aris Moh Muthohir Mulyanto, Edy Munifah Murwoko, F Iwan Setyo Myra Andriana Norman, Maria Bernadette Chayeenee Nova Rijati Nur Rokhman Octaviani, Dhita Aulia Paramita, Cinantya Pulung Nurtantio Andono Putri, Chana Amelinda Rafsanjani, Muhammad Ivan Rifal Winazar Rifal Winazar Roymon Panjaitan Savicevic, Anamarija Jurcev Septiani, Karlina Dwi Shier Nee Saw Sinaga, Daurat Sri Wahyuning Suprapti suprayogi Suprayogi Suprayogi Syah Putra, Fernanda Mulya T.Sutojo Tantik Sumarlin . Taqius Shofi Albastomi Taufik Kurnialensya Triginandri, Rifqi Ubaidillah , Lutfi Utomo, Danang Wahyu Widya Laksana, Deddi Award Yani Parti Astuti Yuli Fitrianto