Taxonomy early detection of brain cancer approach ridge polynomial neural network

Epidemiology of brain cancer data in Indonesia to date is inadequate, this is due to suboptimal diagnostic techniques and incomplete case registration problems. One of the factors causing delays in early detection of brain cancer is the high cost and lack of public knowledge about the risk of brain cancer. The purpose of this research is to develop a method and system that is able to detect brain cancer early using a polynomial neural network ridge algorithm. Ridge polynomial neural network is one algorithm with good accuracy results for early detection of brain cancer from artificial neural network methods. This research will use eight input variables including: headaches gradually becoming more frequent and more severe, nausea and vomiting without cause, impaired memory, seizures, tingling and numbness in the arms and legs, visual disturbances such as blurred vision, related problems with the sense of hearing and impaired balance (difficulty in moving). The data will use weights from time-series and then trained using artificial neural networks with the polynomial neural network ridge algorithm.