THE PERFOMANCE OF THE ARIMAX MODEL ON COOKING OIL PRICE DATA IN INDONESIA
Forecasting is crucial for planning, particularly in addressing potential issues. While ARIMA models are commonly used for time series forecasting, they may need more accuracy by overlooking external factors. The ARIMAX model, which incorporates exogenous variables, is employed to enhance accuracy....
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| Format: | Article |
| Language: | English |
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Universitas Pattimura
2025-04-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14294 |
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| author | Erdanisa Aghnia Ilmani Fida Fariha Amatullah Khairil Anwar Notodiputro Yenni Angraini Laily Nissa Atul Mualifah |
| author_facet | Erdanisa Aghnia Ilmani Fida Fariha Amatullah Khairil Anwar Notodiputro Yenni Angraini Laily Nissa Atul Mualifah |
| author_sort | Erdanisa Aghnia Ilmani |
| collection | DOAJ |
| description | Forecasting is crucial for planning, particularly in addressing potential issues. While ARIMA models are commonly used for time series forecasting, they may need more accuracy by overlooking external factors. The ARIMAX model, which incorporates exogenous variables, is employed to enhance accuracy. This study applies the ARIMAX model to forecast cooking oil prices in Indonesia, known for its complex patterns. Using data from the Directorate General of Domestic Trade and Price Stability (2024), the research highlights fluctuating cooking oil prices from 2010 to 2023 every month. Both ARIMA and ARIMAX models are utilized, with domestic fresh fruit bunch (FFB) prices and the COVID-19 pandemic indicator as exogenous variables. Evaluation based on Mean Absolute Percentage Error (MAPE) shows that the ARIMAX model has a MAPE of 17.31%, compared to 17.69% for the ARIMA model. The lower MAPE value for ARIMAX indicates improved forecasting accuracy by incorporating external factors. Thus, the ARIMAX model is recommended for predicting cooking oil prices, offering better accuracy and valuable insights for policymakers and stakeholders. |
| format | Article |
| id | doaj-art-1a6ef3817f604e7ea2dde9037dac6392 |
| institution | DOAJ |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-1a6ef3817f604e7ea2dde9037dac63922025-08-20T03:05:39ZengUniversitas PattimuraBarekeng1978-72272615-30172025-04-0119281982810.30598/barekengvol19iss2pp819-82814294THE PERFOMANCE OF THE ARIMAX MODEL ON COOKING OIL PRICE DATA IN INDONESIAErdanisa Aghnia Ilmani0Fida Fariha Amatullah1Khairil Anwar Notodiputro2Yenni Angraini3Laily Nissa Atul Mualifah4Statistics and Data Science Department, School of Data Science, Mathematics, and Informatics, IPB University, IndonesiaStatistics and Data Science Department, School of Data Science, Mathematics, and Informatics, IPB University, IndonesiaStatistics and Data Science Department, School of Data Science, Mathematics, and Informatics, IPB University, IndonesiaStatistics and Data Science Department, School of Data Science, Mathematics, and Informatics, IPB University, IndonesiaStatistics and Data Science Department, School of Data Science, Mathematics, and Informatics, IPB University, IndonesiaForecasting is crucial for planning, particularly in addressing potential issues. While ARIMA models are commonly used for time series forecasting, they may need more accuracy by overlooking external factors. The ARIMAX model, which incorporates exogenous variables, is employed to enhance accuracy. This study applies the ARIMAX model to forecast cooking oil prices in Indonesia, known for its complex patterns. Using data from the Directorate General of Domestic Trade and Price Stability (2024), the research highlights fluctuating cooking oil prices from 2010 to 2023 every month. Both ARIMA and ARIMAX models are utilized, with domestic fresh fruit bunch (FFB) prices and the COVID-19 pandemic indicator as exogenous variables. Evaluation based on Mean Absolute Percentage Error (MAPE) shows that the ARIMAX model has a MAPE of 17.31%, compared to 17.69% for the ARIMA model. The lower MAPE value for ARIMAX indicates improved forecasting accuracy by incorporating external factors. Thus, the ARIMAX model is recommended for predicting cooking oil prices, offering better accuracy and valuable insights for policymakers and stakeholders.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14294arimaxcooking oil pricesforecasting |
| spellingShingle | Erdanisa Aghnia Ilmani Fida Fariha Amatullah Khairil Anwar Notodiputro Yenni Angraini Laily Nissa Atul Mualifah THE PERFOMANCE OF THE ARIMAX MODEL ON COOKING OIL PRICE DATA IN INDONESIA Barekeng arimax cooking oil prices forecasting |
| title | THE PERFOMANCE OF THE ARIMAX MODEL ON COOKING OIL PRICE DATA IN INDONESIA |
| title_full | THE PERFOMANCE OF THE ARIMAX MODEL ON COOKING OIL PRICE DATA IN INDONESIA |
| title_fullStr | THE PERFOMANCE OF THE ARIMAX MODEL ON COOKING OIL PRICE DATA IN INDONESIA |
| title_full_unstemmed | THE PERFOMANCE OF THE ARIMAX MODEL ON COOKING OIL PRICE DATA IN INDONESIA |
| title_short | THE PERFOMANCE OF THE ARIMAX MODEL ON COOKING OIL PRICE DATA IN INDONESIA |
| title_sort | perfomance of the arimax model on cooking oil price data in indonesia |
| topic | arimax cooking oil prices forecasting |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14294 |
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