Abstrak 
Indonesian Financial Data Modeling and Forecasting by Using Econometrics Time Series and Neural Network
Sukono, Yuyun Hidayat, Suhartono, Brodjol Sutijo, Abdul Talib Bin Bon, Sudradjat Supian
Universitas Padjadjaran, Global Journal of Pure and Applied Mathematics Volume 12, Number 4 (2016), ISSN 0973-1768 , pp. 3745–3757, Research India Publications, https://www.ripublication.com/gjpam.htm
Bahasa Inggris
Universitas Padjadjaran, Global Journal of Pure and Applied Mathematics Volume 12, Number 4 (2016), ISSN 0973-1768 , pp. 3745–3757, Research India Publications, https://www.ripublication.com/gjpam.htm
ARIMAX, FFNN, inference statistics, inviation, R2incremental
In recent years, many researchers have been using neural network (NN) model as an instrument of their research. The motivation behind the application of NN is that it can be used to solve any application problem, such as pattern recognition, signal processing, process control and forecasting. Inference statistics procedure, testing hypothesis, parameter distribution and cross validation have been developed to select the best NN model. The aim of this research is to develop NN modeling in statistic structure modeling and apply it to the in?ation data in Indonesia. This research is about optimizing the development of Feed Forward Neural Network (FFNN) model procedure and its application. FFNN Model and Time series model are evaluated based on RMSE, MAD and MAPE. The Best model is the one with minimum RMSE, MAD and MAPE. One of the results is a new procedure based on statistics inference, R2 Incremental test, in NN model especially FFNN modeling. The comparison between FFNN model and time series model shows that FFNN model is better than time series model.