Analysis of Neural Network Classification Algorithm to Know the Success Level of Immunotherapy

Abstract

Cancer is a disease that is feared by humans at this stage, the genetic term of most diseases that have the characteristics of abnormal cell growth and beyond the normal cell limits so that they can attack cells that cover and are able to spread to other organs. For cancer recovery therapy is immunization therapy. Of course in this alternative treatment still needs to be done research to determine the level of success with existing conditions and parameters. Increasingly sophisticated, developing technology that helps human work. The neural network algorithm is used to analyze large datasets, the purpose of this study is to find the accuracy and immunotherapy methods of the dataset using a neural network learning machine with 200 data training cycles, 0.9 momentum and 0.01 learning levels that produce quite high accuracy 80 % and AUC value of 0.738

Komparasi Algoritma Random Forest dan Decision Tree untuk Memprediksi Keberhasilan Immunotheraphy

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