Interval is the main component in time series forecasting, hence a Fuzzy Sliding Window Forecasting Method (SWM) suggested in obtaining intervals of forecasting in the Fuzzy Time Series (FTS). Formerly, almost all the intervals were calculated using class frequency. The intervals are then regrouping into the sub-intervals using the provided category. Whereas in this study, the prediction of interval obtained by embedding the idea of SWM into FTS forecasting. The intention of this suggested method is to further improve the success of a time series forecast and indirectly increase forecasting precision. The daily prices of Crude Palm Oil (CPO) data are taken for verification purposes. Hence, the precision of the suggested method is differentiating the existing forecasting method. The outcome of this method is compared to the other methods and it reveals that the suggested method produces precise intervals determination. The discovery of this study can be used as a replacement of existing forecasting method to get an improved prediction interval
