Implementasi Algoritma Learning Vector Quantization untuk Deteksi Dini Penyakit Mata

The eye is one of the senses of human vision that is very important in human life. The lack of online eye health consultation services is often ignored by the public because it considers eye diseases not to be dangerous diseases and have no impact on everyday life. On this issue, then developed an eye disease detection system using the Learning Vector Quantization method. (LVQ). This method is capable of giving a classification of patterns that would represent a particular class. In this study, there are 25 symptoms and 10 eye diseases that will be processed in training and testing with the data being divided into training and test data. The LVQ method will perform several steps to obtain the final weight. Using the LVQ method, the parameter values obtained include Learning rate 0.1, 0.2, Iteration 1 and 2. In the accuracy test of this system, the average accuracy result received with the training data 90 Iterations 2 Learning rates 0.1, testing of the test data 19 yielded accuration of 100% and Iterating 2 Learning rate 0,2 testing of testing data 19 was accurate of 100%. which indicates that the system can function properly. So the LVQ method can be applied to the classification of eye diseases.