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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Public Health Science (IJPHS) Journal of Internet and Software Engineering Jurnal Informatika: Jurnal Pengembangan IT
Divi Galih Prasetyo Putri
Institut Teknologi Sepuluh Nopember
Computer Science & IT Engineering Health Professions

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Journal : Jurnal Informatika: Jurnal Pengembangan IT

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SCANOCULAR: Application for Early Detection of Eye Diseases Using AI and Blockchain Technology Pratomo, Dinar Nugroho; Alfian, Ganjar; Putri, Divi Galih Prasetyo; Kusnady, Rasyid; Pinandhita, Pudyasta Satria; Yusuf, Muhammad Abyan Farras; Dharmawan, Edeline Felicia; Zhafarizza, Ghifari Nafhan Muhammad
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.8014

Abstract

Eye diseases such as cataracts, glaucoma, and diabetic retinopathy affect approximately 2.2 billion people globally, with 1 billion cases being preventable. In Indonesia, cataracts remain the leading cause of blindness. This research presents SCANOCULAR, a mobile application that integrates artificial intelligence (AI) and blockchain technology for early detection of eye diseases. The system utilizes a modified EfficientNetB4 Convolutional Neural Network (CNN) for analyzing eye images, achieving 95.50% accuracy, 95.92% precision, and 94.95% recall in cataract detection with an AUC of 0.9932. The blockchain implementation using Polygon Amoy platform ensures secure data transmission and storage while maintaining efficient transaction processing. Testing results demonstrate the system's capability in identifying various eye conditions while maintaining data integrity through blockchain verification. SCANOCULAR contributes to informatics by implementing a hybrid AI-blockchain architecture optimized for medical imaging applications, with a lightweight CNN model design that reduces computational requirements while maintaining diagnostic accuracy. This integration of technologies provides a potential solution for improving accessibility to eye disease screening and early intervention in Indonesia.
Co-Authors Afidah, Azza Ulil Alfian, Ganjar Ananda, Shafira Putri Budi Bayu Murti Dharmawan, Edeline Felicia Jasmin, Gabriela Anggerita Kusnady, Rasyid Muhammad Fakhrurrifqi Pinandhita, Pudyasta Satria Pratomo, Dinar Nugroho Putra, Jimmy Trio Putri, Salmania Jesamine Saputra, Yuris Mulya Savitri Citra Budi Wahyono Wahyono Widhy Hayuhardhika Nugraha Putra Wijayanti, Risti Yusuf, Muhammad Abyan Farras Zhafarizza, Ghifari Nafhan Muhammad