JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI
Vol. 17 No. 2 (2021): JANUARY 2021

Forecasting Bank Indonesia Currency Inflow and Outflow Using ARIMA, Time Series Regression (TSR), ARIMAX, and NN Approaches in Lampung

Laila Qadrini (Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Sulawesi Barat)
Asrirawan Asrirawan (Unknown)
Nur Mahmudah (Unknown)
Muhammad Fahmuddin (Unknown)
Ihsan Fathoni Amri (Unknown)



Article Info

Publish Date
23 Dec 2020

Abstract

There are various types of data, one of which is the time-series data. This data type is capable of predicting future data with a similar speed as the forecasting method of analysis.  This method is applied by Bank Indonesia (BI) in determining currency inflows and outflows in society. Moreover, Inflows and outflows of currency are monthly time-series data which are assumed to be influenced by time. In this study, several forecasting methods were used to predict this flow of currency including ARIMA, Time Series Regression (TSR), ARIMAX, and NN. Furthermore, RMSE accuracy was used in selecting the best method for predicting the currency flow. The results showed that the ARIMAX method was the best for forecasting because this method had the smallest RMSE.

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Journal Info

Abbrev

jmsk

Publisher

Subject

Mathematics

Description

Jurnal ini mempublikasikan paper-paper original hasil-hasil penelitian dibidang Matematika, Statistika dan Komputasi ...