Page 96 - Contributed Paper Session (CPS) - Volume 6

CPS1832 Nur Fazliana Rahim et al.
4. Discussion and Conclusion
This research presents the field of data driven FRBS in forecasting of Foreign
Exchange Rate (FER). It shows that this new approach gave so much
advantages to strengthen the prior method. A preliminary data driven FRBS,
Weighted Subsethood-Based Algorithm (WSBA) was developed using fuzzy
subsethood values. Its provide easiness by generating default fuzzy rules
without the need to use any threshold value. This is very valuable in forecasting
area, which needs a system that is easy to understand by the people especially
for forecaster. The FER data were process first by classifying the outcomes (FER
rank). By using the rules generated, the FER forecasting was done and were
compared with the prior method. These methods were evaluate using Mean
Squared Error (MSE) and Root Mean Squared Error (RMSE). As mention in the
result, the value of MSE and RMSE results for the proposed WSBA were lesser
than the other method. It can be summarizing that WSBA produce more
effective and reduce forecasting error compare to the prior method. Thus, the
use of this method will lead to the formation of a systematic approach in
forecasting application, which help reinforce decision made by alternative
methods.

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