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Cancer is a major challenge for mankind. Cancer can affect various parts of the body. This deadly disease can be detected in people of all ages. However, the risk of cancer increases with increasing age. Breast cancer is the most common cancer among women, and form largest cause of death for women as well. Then there are problems in the detection of breast cancer, resulting in the patient experiencing unnecessary treatment and cost. Insimilar studies, there are several methods used but there are problems due to the shape of the cancer cells are nonlinear. Neural networks can solve these problems, but neural network is weak in terms of determining the value of the parameter, so it needs to be optimized. Genetic algorithm is one of the optimization methods is good, therefore the values â€‹â€‹of the parameters of the neural network will be optimized by using a genetic algorithm so as to get the best value of the parameter. Neural Network-based GA algorithm has the higher accuracy value than just using Neural Network algorithm. This is evident from the increase in value for the accuracy of the model Neural Network algorithm by 95.42% and the accuracy of algorithm-based Neural Network algorithm GA (Genetic Algorithm) of 96.85% with a difference of 1.43% accuracy. So it can be concluded that the application of Genetic Algorithm optimization techniques to improve the accuracy values on Neural Network algorithm.
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