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| dc.description.abstract | There are some techniques of soft computing that can be used to forecast the data, they
are fuzzy time series, neural network, and genetic algorithm. The methods can solve the data
forecasting in the complex model that related to non linear time series model. In this research, the
forecasting method that used is the Algorithm of Fuzzy Time Series Using Percentage Change As
Universe Discourse that proposed by Stevenson and Porter who will compared with one of the
classical forcasting method. The data that used is data of Indonesia gas consumption years 1990-2013,
where the data contain trend pattern. For that, one of the good classical forecasting method that can
be used is the method of Double Exponential Smoothing Holt. The results, forcasting by using the
Algorithm of Fuzzy Time Series Stevenson Porter is better compared with using the method of Double
Exponential Smoothing Holt, because it has smaller MAPE and MSE value, each of them in a row are
6,56 and 4,93. Where obtained the forecasting result for year 2014 is 38,39 | in_ID |
