KLASIFIKASI PENYAKIT MATA MENGGUNAKAN ALGORITMA CNN DENGAN PRE-TRAINED MODEL VGG-16 DAN VGG-19

The eye is one of the parameters that determine the health of the body. In the eye there are neuron and other parts which are very vulnerable to various diseases. Previously, many studies have done classification for eye disease using the CNN algorithm. However, there is no research that classifies by combining VGG16 and VGG19 model as well differences data using augmentation and data without using augmentation. Therefore, this research focuses on the classification of eye diseases with transfer learning techniques using CNN architecture with Pre-Trained models VGG16, VGG19. The main purpose of this research is to compare the two models to find the most optimal model performance results in handling related cases. Based on the results of the research that has been done, the best accuracy is obtained in scenarios with data that has been augmented. Where the VGG16 model achieved 94% accuracy, and VGG19 with 93% accuracy.