The simulation was implemented to find out the perfomance for a combination of methods in Stevenson-Porter-Cheng Fuzzy
Time Series (FTS) based on 100 replicates on 100 generated data following the model of ARIMA (1,0,0) or AR (1). There are 9
scenarios used as a combination between 3 data generation error variance values (0.5, 1, 3) and 3 AR(1) parameter values i.e. 0.3, 0.5,
and 0.7. The results of the simulation showed the greater variance of error and the value of the of AR(1) parameter then the variance of
the MSE results with ARIMA will be even greater (0.0634 – 15.7633). While the variance of the MSE results forecasting with Cheng
and Cheng2 (no sub interval) FTS tend to be more stable (0.0712 – 2.9648 and 0.0640 – 2.7157). By using the percentage change of
historical data as the set of universe, SP Cheng FTS produces MSE forecasting range values ranging from 0.0722 – 14.7045. While SP
Cheng2 FTS using the difference of historical data resulted in MSE forecasting values ranging from 0.0759 – 4.6803. Although both
MSE values do not look much better than Cheng and Cheng2 FTS, but the greater the AR(1) parameter then MSE forecasting of Cheng
and Cheng2 FTS will be better than ARIMA and even closer to the Cheng and Cheng2 FTS.
Published In:IJCSN Journal Volume 6, Issue 6
Date of Publication : December 2017
Pages : 806-811
Tables : --
Wahyu Dwi Sugianto : currently pursuing masters degree program
in Applied Statistics in Bogor Agricultural University, Indonesia.
Attained bachelor degree from STIS Jakarta in 2006.
Agus Mohamad Soleh : is lecturer at Department of Statistics,
Bogor Agricultural University, Indonesia. His main interest is in
Data Mining, Statistical Computation and Statistical Modelling.
Farit Mochamad Afendi : is lecturer at Department of Statistics,
Bogor Agricultural University, Indonesia. Her main interest is in
ARIMA, Cheng Fuzzy Time Series, Simulation, Stevenson-Porter
The results of forecasting with simulation of generated
data with ARIMA(1,0,0) or AR(1) with non zero means
using 9 scenarios of different (0.5, 1, 3) and 3
parameters ??1 (0.3, 0.5, 0.7) showed that the increased
and AR(1) parameter, then the variance of MSE with
ARIMA also increased in the range of 0.0634 – 15.7633.
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