GENERAL REGRESSION NEURAL NETWORK (GRNN) PADA PERAMALAN DATA TIME SERIES; GENERAL REGRESSION NEURAL NETWORK (GRNN) IN TIME SERIES FORECASTING DATA

Luh Putu Widya Adnyani, Subanar

2012 | Disertasi | PROGRAM STUDI S2 MATEMATIKA

General Regression Neural Network (GRNN) is one method that was developed from the concept of artificial neural network that can be used for forecasting. This method was applied to predict the time series data that has a causal relations where the forecasting method used previously (ARIMA BOXJenkins) is not able to explain the presence of linkage data. This research was conducting by taking the dollar exchage rate and composite stock price index(IHSG). By using the GRNN methode will obtained the predictive value in some future periode. The advantages using this method is faster in term of computation and doesn’t requared the presence of a data asumptions. GRNN method produces more accurate predictive value comapred with ARIMA. It was shown that the MSE value is smaller than ARIMA

Kata Kunci : GRNN, Neural Network; GRNN Time Series; GRNN Kurs dan IHSG