BibTex Citation Data :
@article{J.Gauss14697, author = {Johan Wicaksana and Hasbi Yasin and Sudarno Sudarno}, title = {PROBABILISTIC NEURAL NETWORK BERBASIS GUI MATLAB UNTUK KLASIFIKASI DATA REKAM MEDIS (Studi Kasus Penyakit Diabetes Melitus di Balai Kesehatan Kementerian Peridustrian Jakarta)}, journal = {Jurnal Gaussian}, volume = {5}, number = {3}, year = {2016}, keywords = {Neural Network, Probabilistics Neural Network, diabetes mellitus, GUI, holdout, smoothing parameter}, abstract = { Neural Network (NN) system is an information-processing that has characteristics similar to the neural network in living beings. A model of Neural Network is used for classification is Probabilistic Neural Network (PNN). PNN structured by four layers, the input layer, layer pattern, the summation layer and output layer. One of classification problems that can be solved by PNN is a classification of Diabetes Mellitus’s status. Diabetes mellitus is a chronic disease that occurs either when the pancreas does not produce enough insulin or when the body cannot effectively use the insulin produced. To facilitate the classification of diabetes mellitus, it is used a software-based Graphical User Interface (GUI) of Matlab to build a software of PNN. GUI that is formed can do PNN classification and predict the status of one’s Diabetes Mellitus. PNN structure that is formed resulting the highest accuracy 0.9143548 on the training process and 0.919512 on the testing process obtained by the percentage of training data than testing data by 90%:10% with holdout accuracy evaluation method, and a smoothing value of 1. This classification resulting 23 patients were classified as negative diabetes and 18 patients were classified as positive diabetes. Keywords : Neural Network, Probabilistics Neural Network, diabetes mellitus, GUI, holdout, smoothing parameter. }, issn = {2339-2541}, pages = {427--436} doi = {10.14710/j.gauss.5.3.427-436}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/14697} }
Refworks Citation Data :
Neural Network (NN) system is an information-processing that has characteristics similar to the neural network in living beings. A model of Neural Network is used for classification is Probabilistic Neural Network (PNN). PNN structured by four layers, the input layer, layer pattern, the summation layer and output layer. One of classification problems that can be solved by PNN is a classification of Diabetes Mellitus’s status. Diabetes mellitus is a chronic disease that occurs either when the pancreas does not produce enough insulin or when the body cannot effectively use the insulin produced. To facilitate the classification of diabetes mellitus, it is used a software-based Graphical User Interface (GUI) of Matlab to build a software of PNN. GUI that is formed can do PNN classification and predict the status of one’s Diabetes Mellitus. PNN structure that is formed resulting the highest accuracy 0.9143548 on the training process and 0.919512 on the testing process obtained by the percentage of training data than testing data by 90%:10% with holdout accuracy evaluation method, and a smoothing value of 1. This classification resulting 23 patients were classified as negative diabetes and 18 patients were classified as positive diabetes.
Keywords: Neural Network, Probabilistics Neural Network, diabetes mellitus, GUI, holdout, smoothing parameter.
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