Classification of Eye Diseases Using the AlexNet Convolutional Neural Network Model Algorithm

  • Moch Deny Pratama Universitas Negeri Surabaya Surabaya, Indonesia
  • Royal Fajar Sultoni Universitas Pembangunan Nasional Veteran, Jawa Timur, Surabaya, Indonesia
  • Adil Sandy Wardhani Universitas Pembangunan Nasional Veteran, Jawa Timur, Surabaya, Indonesia
  • Maulana Hassan Sechuti Universitas Pembangunan Nasional Veteran, Jawa Timur, Surabaya, Indonesia
  • Yerezqy Bagus Universitas Pembangunan Nasional "Veteran" Jawa Timur
  • Dina Zatusiva Haq
  • Yoga Ari Tofan
DOI: https://doi.org/10.33005/ijconsist.v7i1.160
Keywords: Classification of Eye Diseases, Convolutional Neural Network, Alexnet, Deep Learning

Abstract

This study uses the Convolutional Neural Network (CNN) method with the AlexNet model to classify eye diseases based on medical images. The dataset includes labeled images of three types of eye diseases: cataract, glaucoma, and diabetic retinopathy. The experimental results show that the model achieved an accuracy of 75.18%, which indicates that CNN with the AlexNet architecture can classify eye diseases quite well. This research shows that deep learning can be used to help doctors or health professionals in diagnosing eye diseases through automatic image analysis. Although the accuracy still needs to be improved, this study can serve as a reference for developing an automated diagnostic system in the future. Further research is expected to increase accuracy, expand the dataset, and apply other deep learning techniques to improve the performance of eye disease detection.

Published
2025-11-05
How to Cite
Pratama, M. D., Sultoni, R. F., Wardhani, A. S., Sechuti, M. H., Yerezqy Bagus, Dina Zatusiva Haq, & Yoga Ari Tofan. (2025). Classification of Eye Diseases Using the AlexNet Convolutional Neural Network Model Algorithm. IJCONSIST JOURNALS, 7(1), 22-28. https://doi.org/10.33005/ijconsist.v7i1.160
Issue
Vol 7 No 1 (2025): September
Section
Articles

Copyright (c) 2025 Moch Deny Pratama, Royal Fajar Sultoni, Adil Sandy Wardhani, Maulana Hassan Sechuti, Yerezqy Bagus, Dina Zatusiva Haq, Yoga Ari Tofan

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