The Application of The Fuzzy Time Series-Markov Chain Method on Rupiah Exchange Rate Data Against The United States Dollar (USD)
DOI:
https://doi.org/10.24036/ujsds/vol1-iss4/91Keywords:
Exchange Rate, Fuzzy Time Series Markov chain, ForecastAbstract
The exchange rate plays an important role in evaluating the Indonesian economy due to how much it affects the nation's overall financial situation. Activities for projecting future exchange rates can be conducted based on their dynamic characteristics. The purpose of this study is to predict the exchange rate of the Indonesian Rupiah (IDR) against the United States Dollar (USD) using the Fuzzy Time Series Markov chain (FTS-MC) method. Researchers apply the FTS-MC approach to analyze the connection between every bit of historical data and the direction in which it moved in order to forecast future data movements. While the rupiah exchange rate Forecast against the USD between January 2 and January 31, 2023, with a MAPE value of 2.41% and a forecast accuracy score of 97.58% result. During up to 8 forecasted periods, the forecasting value gained by the FTS-MC approach is close to the actual value, and the next period is higher than the current value. The forecasting results graph further shows that the FTS-MC approach gives forecast values fluctuate around IDR15,800.
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Copyright (c) 2023 rahmad revi fadillah, Dony Permana, Yenni Kurniawati, Admi Salma
This work is licensed under a Creative Commons Attribution 4.0 International License.