Comparison between artificial neural network and non-linear auto regressive moving average (NARMA) models for internet traffic / Muhammad Naqiuddin Sahrani

With the rapid development of technology todays, the development of computer and network communication technology also no exceptions change. Due to this development, most applications are accessible internet network. As the result, most people are more comfortable to do their daily activity or task using internet because it more easily to done without moving from one place. As increasing of online user, other problems also have been raised together such as network traffic and might be lead to worsen problem. If this problem occurs, users might have problem to access the server. Predicting internet traffic is one of the solutions that can help to overcome this problem. Countermeasures steps can be taken before any problems occur and can give good quality services to the customers. There are many studies that already done before which the main idea is to predict internet traffic. The differences between these studies are their methods to approach this problem. Most of their study based on Artificial Neural Network and combined with other methods.0 Any changes in network traffic can be detected and can analyses steps can be done to detect the causes of die changes. This study is to approach main problems which to predict internet traffic more effectively using Non-Linear Auto Regressive Moving Average (NARMA) Model. This study will compare two models which are artificial neural network and polynomial of NARMA model. The performance of those NARMA model will be evaluated by using model fitting and model validation tests.