Deep Learning untuk Klasifikasi Diabetic Retinopathy menggunakan Model EfficientNet

SYAMSUL RIZAL, NUR IBRAHIM, NOR KUMALASARI CAESAR PRATIWI, SOFIA SAIDAH, RADEN YUNENDAH NUR FU’ADAH

Sari


ABSTRAK

Diabetic Retinopathy merupakan penyakit yang dapat mengakibatkan kebutaan mata yang disebabkan oleh adanya komplikasi penyakit diabetes melitus. Oleh karena itu mendeteksi secara dini sangat diperlukan untuk mencegah bertambah parahnya penyakit tersebut. Penelitian ini merancang sebuah sistem yang dapat mendeteksi Diabetic Retinopathy berbasis Deep Learning dengan menggunakan Convolutional Neural Network (CNN). EfficientNet model digunakan untuk melatih dataset yang telah di pre-prosesing sebelumnya. Hasil dari penelitian tersebut didapatkan akurasi sebesar 79.8% yang dapat mengklasifikasi 5 level penyakit Diabetic Retinopathy.

Kata kunci: Diabetic Retinopathy, Deep Learning, CNN, EfficientNet, Diabetic Classification

 

ABSTRACT

Diabetic Retinopathy is a diseases which can cause blindness in the eyes because of the complications of diabetes mellitus. Therefore, an early detection for this diseases is very important to prevent the diseases become severe. This research builds the system which can detect the Diabetic Retinopathy based on Deep Learning by using Convolutional Neural Network (CNN). EfficientNet model is used to trained the dataset which have been pre-prossed. The result shows that the system can clasiffy the 5 level of Diabetic Retinopathy with accuracy 79.8%. 

Keywords: Diabetic Retinopathy, Deep Learning, CNN, EfficientNet, Diabetic Classification


Kata Kunci


Diabetic Retinopathy; Deep Learning; CNN; EfficientNet; Diabetic Classification

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Referensi


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DOI: https://doi.org/10.26760/elkomika.v8i3.693

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ISSN (print) : 2338-8323 | ISSN (electronic) : 2459-9638

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Department of Electrical Engineering Institut Teknologi Nasional Bandung

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Contact: +627272215 (ext. 206)

Email: jte.itenas@itenas.ac.id________________________________________________________________________________________________________________________


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