Optimization of Neural Network with Genetic Algorithm for Breast Cancer Classification

Proper diagnosis of breast cancer is one of the main issues in a medical sector. The neural network could overcome the issue, but weak in determining parameter value, therefore it requires optimization. A genetic algorithm is one of the optimization methods, due to that matter, attribute parameter value of neural network will be optimized by using Genetic Algorithm to acquire the best predictor attributes. Genetic-based Neural Network algorithm has higher accuracy compared to the application of Neural Network algorithm alone. This notion is proven through the increasing rate of accuracy value for Neural Network algorithm which amounted to 96.57 % and 97.24 % for Genetic-Based Neural Network Algorithm as well as the decreasing rate of error classification of Neural Network algorithm model from 3.43 % rate to 2.86 % due to the application of Genetic-Based Neural Network Algorithm. Therefore, it can be concluded that the application of the optimization technique of Genetic Algorithm can enhance the accuracy value and decrease the error value of the Neural Network algorithm on breast cancer classification.