KAJIAN IDENTIFIKASI MODEL DIAGNOSIS NEUROBLASTOMA DENGAN METODE BACKPROPAGATION DAN PRINCIPAL COMPONENT ANALYSIS
Abstract
Neuroblastoma is a type of embryonal cancer of the nervous system that is mostly found in children. Most etiologies of neuroblastoma are unknown, so many patients undergo treatment at an advanced stage. The importance of detection as early as possible is very necessary in neuroblastoma cancer so that children diagnosed with neuroblastoma can get a good prognosis. Through this study, it is expected to be able to know the feasibility of research with regard to artificial neural network procedures and the proposed PCA method. In this case the desired model is a set of training faces that will be formed through a linear combination in the training Propagation phase using backpropagation artificial neural network algorithms. In this case the desired model is a set of training faces that will be formed through a linear combination in the training Propagation phase using backpropagation artificial neural network algorithm. Backpropagation training by conducting feed-forward from input training patterns, calculations, related errors, and weighting settings based on previous weights
Keywords: literature study, identification, backpropagation, PCA
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