PENINGKATAN NEURAL NETWORK DENGAN FEATURE SELECTION UNTUK PREDIKSI KANKER PAYUDARA - Evy Priyanti (Universitas Bina Sarana Informatika Kota Sukabumi, 2016)
Breast cancer is increasing in everycountries in the world, especially in developing countries likeIndonesia. Neural network is able to solve problems with the accuracy of data and not linear. Neuralnetwork optimization tested weeks to produce the best accuracy value, applying neural network withfeature selection methods such as Wrapper with Backward Elimination to raise the accuracy produced byNeural Network. Experiments conducted to obtain optimal architecture and to increase the value ofaccuracy. Results of the research is a confusion matrix to prove the accuracy of Neural network beforeoptimized by Backward Elimination was 96.42% and 96.71% after becoming optimized. This proves theestimation of feature selection trials using neural network-based method Backward Elimination moreaccurate than the individual neural network method.