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All Journal Jurnal Sains dan Teknologi Techno.Com: Jurnal Teknologi Informasi Jurnal Pseudocode Jurnal Informatika dan Teknik Elektro Terapan CESS (Journal of Computer Engineering, System and Science) Sistemasi: Jurnal Sistem Informasi Jurnal Pilar Nusa Mandiri JUTIK : Jurnal Teknologi Informasi dan Komputer SINTECH (Science and Information Technology) Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal RESISTOR (Rekayasa Sistem Komputer) INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi International Journal of Engineering and Emerging Technology Jurnal Ekonomi Manajemen Sistem Informasi INSERT: Information System and Emerging Technology Journal Prosiding SNAST Jurnal Info Sains : Informatika dan Sains Andalasian International Journal of Applied Science, Engineering, and Technology Jurnal Pendidikan Sains dan Komputer Jurnal Krisnadana Journal of Artificial Intelligence and Digital Business Jurnal Krisnadana Paradharma: Jurnal Aplikasi IPTEK Jurnal ilmiah teknologi informasi Asia JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
I Gusti Ayu Agung Diatri Indradewi
Universitas Pendidikan Ganesha
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Journal : Jurnal Pseudocode

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Klasifikasi Severity Level Diabetic Macular Edema Berbasis ResNet-50 Maysanjaya, I Made Dendi; Pratiwi, Putu Yudia; Indradewi, I Gusti Ayu Agung Diatri
Jurnal Pseudocode Vol 13 No 1 (2026): Volume 13 Nomor 1 Februari 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.13.1.9-13

Abstract

Diabetes is one of the most common diseases people suffer from today, and it can lead to complications such as blindness, heart disease, and kidney failure. The condition of blindness caused by this disease is known as diabetic retinopathy (DR). An ophthalmologist will use a fundus camera to examine the retina, looking for several clinical features, such as microaneurysms (MA), hemorrhages (HM), cotton-wool spots (CWS), and exudates. Based on these clinical symptoms, clinicians then determined the patient's level of diabetic macular edema (DME) severity. Although several studies have applied CNN-based architectures for diabetic retinopathy detection, limited attention has been given to the impact of dataset imbalance handling on DME severity classification, particularly using ResNet-50. This study highlights the significant impact of extensive data augmentation on classification performance in imbalanced DME datasets. Evaluate performance using the accuracy, precision, and recall metrics. We used the IDRiD dataset, which consists of 516 images split into a training set of 413 and a test set of 103. IDRiD divides the dataset into three classes, namely normal, moderate DME, and severe DME. In the preprocessing stage, we enhanced contrast using CLAHE and resized the images to 224x224 pixels. To address the imbalance, we applied 11 data augmentation methods. We experimented by comparing the performance of two models: one with and one without dataset augmentation. Based on the test results, the best performance was obtained with the model that included dataset augmentation, achieving an accuracy of 0.5961, a precision of 0.63, and a recall of 0.61, while the baseline model (without dataset augmentation) gained 0.4553, 0.36, and 0.34 for the accuracy, precision, and recall, respectively.
Co-Authors Adnyana, I Ketut Widhi Andika, I Gede Arakian, Laurensia Anjelina Tutosili Bawatanaya, Anak Agung Gede Wisnu Cahyadi, Kadek Wawan Devi, Made Diah Arista Dewi, Ni Putu Bimantari Dewi, Ni Putu Dita Ariani Sukma Febiasterina, Dyapradita Eka Gede Arna Jude Saskara Gede Surya Mahendra I Gde Prayoga Wibawa I Gede Mahendra Darmawiguna I Kadek Wahyu Dananjaya I ketut Gede Darma Putra I Ketut Resika Arthana I Made Ardwi Pradnyana I Made Gede Sunarya I Md. Dendi Maysanjaya I Putu Agung Bayupati Ida Bagus Nyoman Pascima Kertiyasa, Made Medhi Premana Komang Pramayasa Made Suci Ariantini Made Windu Antara Kesiman Mitha, I Made Ardha Premana Ni Kadek Ariasih, Ni Kadek Ni Luh Wiwik Sri Rahayu Ginantra Ni Putu Sri Mulyani Ni Wayan Wardani Putra, I Kadek Andika Putra, I Wayan Ari Pramana Putri, Vany Adelia Putu Yudia Pratiwi Raditia, Kadek Rama Rajasyah, Alfatino Yohan Saraswati, Ni Wayan Sumartini Sari, Ni Luh Pangestu Widya suryani, rika Sutrisna, Ketut Dita Ari Wardani, Ni Wayan Wayan Gede Suka Parwita