PENERAPAN ALGORITMA MULTILAYER PERCEPTRON UNTUK DETEKSI DINI PENYAKIT DIABETES - Ahmad Setiadi (Paradigma, 2012)
Each year, patient of diabetes mellitus is increasing, so that is needed the diagnose technique which is effective to detect in early. Neural network as a model of data mining can be used to predict wether someone is suffered from diabetes mellitus or not. In this research, Multilayer Perceptron (MLP) as a neural network algorithm is used, not only because this algorithm has agood ability in predicting but also because this algorithm is commonly used. In this research, the processed data is total of 768 records and as a result of checking up Indian Pima women at least 21 years old.. To implement the MLP algorithm, SPSS Neural Network 17.0 is used. The result of implementing algorithm then is evaluated by using confusion matrix method and ROC (Receiver Operating Characteristic) curve method. This result is proved that implementation of MLP algorithm to detect diabetes mellitus for Indian Pima has a good performance. The value of accuracy by confusion matrix method is 77,7 %. Using ROC curve method, this research shows the accuracy of 0,83, so that it is including as good classification because it is being among 0,8 until 0,9. This research proved that MLP Algorithm can be used to detect diabetes mellitus in early time.Keywords: diabetes mellitus, neural network model, multilayer perceptron, confusion matrix, kurva ROC