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https://doi.org/10.1109/eecsi....
Article . 2017 . Peer-reviewed
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Prediction of Rupiah Against US Dollar by Using ARIMA

Authors: Adiba Qonita; Annas Gading Pertiwi; Triyanna Widiyaningtyas;

Prediction of Rupiah Against US Dollar by Using ARIMA

Abstract

The currency exchanges rate is one of the most important things in the economy. The currency exchange rate is needed in the business word for example, investment and profit assessment. Prediction of rupiah rate is done to get the price of the rupiah against US dollar in the future to be used as consideration in decision-making, thereby reducing the risk of loss. Therefore, we need a method that can help in making business decisions about when to make the right trades with a high degree of accuracy. This study aims to predict the value of rupiah against US dollar by using ARIMA (Autoregressive Integrated Moving Average). This study uses four stages, including (1) the preparation of the dataset, (2) preprocessing of data, (3) the use of ARIMA models, (4) test accuracy. The data used for the test is the data rate from January 4th 2010 until June 24th 2016. The result showed that ARIMA method has an accuracy rate of 98.74%. Based on the result, it can be concluded that the development of the predictive value of the rupiah against the US dollar using ARIMA method was accurate to use.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Top 10%
bronze