Application of the Fuzzy Time Series-markov Chain Method to the Rupiah Exchange Rate Against the US Dollar (USD)

UNP Journal of Statistics and Data Science Pub Date : 2023-08-28 DOI:10.24036/ujsds/vol1-iss4/91

None Rahmad revi fadillah, None Dony Permana, None Yenni Kurniawati, None Admi Salma

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Abstract

The exchange rate holds great significance in analyzing the Indonesian economy, given its substantial influence on the overall economic landscape. By virtue of its dynamic characteristics, it is possible to engage in forecasting activities to anticipate forthcoming exchange rates. The aim of this research is to develop a prediction model using the Fuzzy Time Series (FTS) Markov chain method to forecast the Indonesian Rupiah's exchange rate against the US Dollar. Additionally, the study intends to determine the projected exchange rate of the Rupiah against the US Dollar for the upcoming season. Using the Fuzzy Time Series (FTS) Markov Chain method, the values of and , which are precise positive numbers, are determined by the researcher. Forecasting this level of sales result with =44.38 and = 11 generate error values (MAPE) of 0.2627525%. Forecasting for the next 21 days compared to data on sales of the rupiah against the USD dollar from January 2 2023 to January 31 2023 produces a MAPE value of 2.414564% with an accuracy rate of 97.58544%.

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模糊时间序列-马尔可夫链方法在印尼盾对美元汇率计算中的应用

鉴于汇率对整体经济格局的重大影响，它对分析印尼经济具有重要意义。由于其动态特性，有可能进行预测活动，以预测即将到来的汇率。本研究的目的是建立一个使用模糊时间序列(FTS)马尔可夫链方法的预测模型来预测印尼盾对美元的汇率。此外，该研究还打算确定下一季印尼盾对美元的预计汇率。利用模糊时间序列(FTS)马尔可夫链方法，由研究人员确定和的精确正数值。用=44.38和= 11预测这一水平的销售结果产生的误差值(MAPE)为0.2627525%。与2023年1月2日至2023年1月31日印尼盾兑美元的销售数据相比，预测未来21天的MAPE值为2.414564%，准确率为97.58544%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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UNP Journal of Statistics and Data Science

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