DIAGNOSIS PENYAKIT DIABETES RETINOPATI BERDASARKAN KOMBINASI ALGORITME MULTILAYER PERCEPTRON DAN CORRELATION-BASED FEATURE SELECTION

Retinopati diabetes is one of complications diabetes mellitus that most common cause of permanent blindness. The longer the disease diabetes mellitus the possibility of suffering from the retinopati diabetes will get bigger. Diagnose of disease using conventional way is considered less effective so that utilizes computer-based system as an alaysis techniques, one of them is data mining science. In this research aims to know the level of accuracy and computional load against the algorithm being used. In this research the diagnosis is done using combination of Multilayer Perceptron (MLP) algorithms and Correlations-based Features Selection on the messidor-features dataset with weka tools. The result showed the accuracy before the feature selection is 72.02% with a time of 2.46 second and after feature selection the accuracy 73.24% with a time 0.98 second. The evaluation result using ROC curve shows that the combination of Multilayer Perceptron algorithms and Correlation-based Feature Selection are included in the category fair classification.