Application of ARIMA (Autoregressive Integrated Moving Average) model to predict Rupiah selling exchange rate against US Dollar
Currency is a tool in the form of money that is accepted and valid and legal as a payment and economic transactions in a country. US dollar is benchmark for world currencies, so predicting rupiah against US dollar is important. The purpose of this study is to analyze the characteristics of daily sel...
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FoundAE
2023-12-01
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| Series: | International Journal of Applied Mathematics, Sciences, and Technology for National Defense |
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| Online Access: | https://journal.foundae.com/index.php/JAS-ND/article/view/225 |
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| author | Afif Febriawan Fitria Virgantari Isti Kamila Eduard Taganap |
| author_facet | Afif Febriawan Fitria Virgantari Isti Kamila Eduard Taganap |
| author_sort | Afif Febriawan |
| collection | DOAJ |
| description | Currency is a tool in the form of money that is accepted and valid and legal as a payment and economic transactions in a country. US dollar is benchmark for world currencies, so predicting rupiah against US dollar is important. The purpose of this study is to analyze the characteristics of daily selling rate Rupiah against US Dollar, determine best model, and make predictions selling rate of Rupiah against US Dollar. Data used is daily data on selling rate of Rupiah against US Dollar 20 November 2020 - 19 January 2023 with details data training 20 November 2020 - 20 November 2022 and data testing 21 November 2022 - 19 January 2023. The model used is Autoregressive Integrated Moving Averages (ARIMA). The best model was chosen based on the smallest Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Akaike Information Criterion (AIC). From the analysis results, it is found that best model is ARIMA (2,1,2) because it has significant parameters, white-noise residuals and has smallest MSE and MAPE values. With ARIMA model (2,1,2) the forecasting results for January 20 2023 – January 31 2023 is obtained with highest selling price on January 30 2023 Rp.15,932.4 and smallest on January 20 2023 Rp.15,901.9 and the average Rp.15,919.4. Based on these results, exporters and importers can consider their business activities. |
| format | Article |
| id | doaj-art-7a7f7c1aa7364749ace59dedfae2aaf6 |
| institution | Kabale University |
| issn | 2986-0776 2985-9352 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | FoundAE |
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| series | International Journal of Applied Mathematics, Sciences, and Technology for National Defense |
| spelling | doaj-art-7a7f7c1aa7364749ace59dedfae2aaf62025-08-20T03:52:38ZengFoundAEInternational Journal of Applied Mathematics, Sciences, and Technology for National Defense2986-07762985-93522023-12-011310711810.58524/app.sci.def.v1i3.225144Application of ARIMA (Autoregressive Integrated Moving Average) model to predict Rupiah selling exchange rate against US DollarAfif Febriawan0Fitria Virgantari1Isti Kamila2Eduard Taganap3Program Studi Matematika, FMIPA, Universitas PakuanProgram Studi Matematika, FMIPA, Universitas PakuanProgram Studi Matematika, FMIPA, Universitas PakuanDepartment of Mathematics and Physics, Central Luzon State University, Science City of Mun˜oz, Nueva Ecija 3120, PhilippinesCurrency is a tool in the form of money that is accepted and valid and legal as a payment and economic transactions in a country. US dollar is benchmark for world currencies, so predicting rupiah against US dollar is important. The purpose of this study is to analyze the characteristics of daily selling rate Rupiah against US Dollar, determine best model, and make predictions selling rate of Rupiah against US Dollar. Data used is daily data on selling rate of Rupiah against US Dollar 20 November 2020 - 19 January 2023 with details data training 20 November 2020 - 20 November 2022 and data testing 21 November 2022 - 19 January 2023. The model used is Autoregressive Integrated Moving Averages (ARIMA). The best model was chosen based on the smallest Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Akaike Information Criterion (AIC). From the analysis results, it is found that best model is ARIMA (2,1,2) because it has significant parameters, white-noise residuals and has smallest MSE and MAPE values. With ARIMA model (2,1,2) the forecasting results for January 20 2023 – January 31 2023 is obtained with highest selling price on January 30 2023 Rp.15,932.4 and smallest on January 20 2023 Rp.15,901.9 and the average Rp.15,919.4. Based on these results, exporters and importers can consider their business activities.https://journal.foundae.com/index.php/JAS-ND/article/view/225time series modelselling ratearima |
| spellingShingle | Afif Febriawan Fitria Virgantari Isti Kamila Eduard Taganap Application of ARIMA (Autoregressive Integrated Moving Average) model to predict Rupiah selling exchange rate against US Dollar International Journal of Applied Mathematics, Sciences, and Technology for National Defense time series model selling rate arima |
| title | Application of ARIMA (Autoregressive Integrated Moving Average) model to predict Rupiah selling exchange rate against US Dollar |
| title_full | Application of ARIMA (Autoregressive Integrated Moving Average) model to predict Rupiah selling exchange rate against US Dollar |
| title_fullStr | Application of ARIMA (Autoregressive Integrated Moving Average) model to predict Rupiah selling exchange rate against US Dollar |
| title_full_unstemmed | Application of ARIMA (Autoregressive Integrated Moving Average) model to predict Rupiah selling exchange rate against US Dollar |
| title_short | Application of ARIMA (Autoregressive Integrated Moving Average) model to predict Rupiah selling exchange rate against US Dollar |
| title_sort | application of arima autoregressive integrated moving average model to predict rupiah selling exchange rate against us dollar |
| topic | time series model selling rate arima |
| url | https://journal.foundae.com/index.php/JAS-ND/article/view/225 |
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