1. Singh fuzzy time series high order method analysis on forecasting the export value in DKI Jakarta Province.
- Author
-
Ferdias, Pandri and Randri, Muhamad Deva
- Subjects
- *
LOGIC , *TIME series analysis , *FORECASTING , *SIMPLICITY , *PROVINCES - Abstract
S.R. Singh presented in 2009, a high-order fuzzy time series that served as the foundation for a computational forecasting approach. The new computational technique overcomes the drawbacks of previous high-order fuzzy time series models more effectively. Its simplicity is enhanced by the use of a w-step fuzzy predictor as the forecasting parameter, rather than costly computations of fuzzy logical relations and deviations in successive values of several orders. This approach is used to decide which order is preferable by evaluating the forecasting model using sMAPE on DKI Jakarta Province export value data from January 2017 to May 2022. When compared to the other orders, the seventh order has the lowest SMAPE of 2.626%. In this case, S.R. Singh Fuzzy Time Series order 7 delivers better and more accurate results than other orders. Furthermore, S.R. Singh Fuzzy Time Series may be used with data that has cyclical patterns as well as data that has monthly time intervals. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF