PERFORMANCE COMPARISON OF SARIMA INTERVENTION AND PROPHET MODELS FOR FORECASTING THE NUMBER OF AIRLINE PASSENGER AT SOEKARNO-HATTA INTERNATIONAL AIRPORT
The impact of the COVID-19 pandemic on the air transportation sector, particularly Soekarno-Hatta (Soetta) International Airport, has been quite significant. The number of passengers at Soetta Airport has decreased due to the COVID-19 pandemic, but flight activities are still ongoing to this day. An...
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Universitas Pattimura
2023-12-01
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9593 |
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| author | Vivin Nur Aziza Fatma Hilali Moh'd Firda Aulia Maghfiroh Khairil Anwar Notodiputro Yenni Angraini |
| author_facet | Vivin Nur Aziza Fatma Hilali Moh'd Firda Aulia Maghfiroh Khairil Anwar Notodiputro Yenni Angraini |
| author_sort | Vivin Nur Aziza |
| collection | DOAJ |
| description | The impact of the COVID-19 pandemic on the air transportation sector, particularly Soekarno-Hatta (Soetta) International Airport, has been quite significant. The number of passengers at Soetta Airport has decreased due to the COVID-19 pandemic, but flight activities are still ongoing to this day. An accurate forecasting model is needed to predict the number of airline passengers at Soetta Airport with the presence of the COVID-19 pandemic as an intervention. In this study we discuss performance comparison of two models namely SARIMA intervention and Prophet in forecasting the number of domestic passengers at Soetta Airport. The research results showed that the best SARIMA intervention model was SARIMA (0,1,1)(1,0,0)12 b = 0, s = 20, r = 0, with a Mean Absolute Percentage Error (MAPE) of 28% and Root Mean Square Error (RMSE) of 433473. On the other hand, the Prophet model yielded a MAPE of 37% and an RMSE of 497154. In terms of MAPE and RMSE, the SARIMA intervention method provides better results than the Prophet model in forecasting the number of domestic passengers at Soetta Airport. |
| format | Article |
| id | doaj-art-0d75030c9b024b4ea486fb153dcffb5d |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-0d75030c9b024b4ea486fb153dcffb5d2025-08-20T03:36:37ZengUniversitas PattimuraBarekeng1978-72272615-30172023-12-011742107212010.30598/barekengvol17iss4pp2107-21209593PERFORMANCE COMPARISON OF SARIMA INTERVENTION AND PROPHET MODELS FOR FORECASTING THE NUMBER OF AIRLINE PASSENGER AT SOEKARNO-HATTA INTERNATIONAL AIRPORTVivin Nur Aziza0Fatma Hilali Moh'd1Firda Aulia Maghfiroh2Khairil Anwar Notodiputro3Yenni Angraini4Departement of Statistics, Faculty of Mathematics and Natural Sciences, IPB University, IndonesiaDepartement of Statistics, Faculty of Mathematics and Natural Sciences, IPB University, IndonesiaDepartement of Statistics, Faculty of Mathematics and Natural Sciences, IPB University, IndonesiaDepartement of Statistics, Faculty of Mathematics and Natural Sciences, IPB University, IndonesiaDepartement of Statistics, Faculty of Mathematics and Natural Sciences, IPB University, IndonesiaThe impact of the COVID-19 pandemic on the air transportation sector, particularly Soekarno-Hatta (Soetta) International Airport, has been quite significant. The number of passengers at Soetta Airport has decreased due to the COVID-19 pandemic, but flight activities are still ongoing to this day. An accurate forecasting model is needed to predict the number of airline passengers at Soetta Airport with the presence of the COVID-19 pandemic as an intervention. In this study we discuss performance comparison of two models namely SARIMA intervention and Prophet in forecasting the number of domestic passengers at Soetta Airport. The research results showed that the best SARIMA intervention model was SARIMA (0,1,1)(1,0,0)12 b = 0, s = 20, r = 0, with a Mean Absolute Percentage Error (MAPE) of 28% and Root Mean Square Error (RMSE) of 433473. On the other hand, the Prophet model yielded a MAPE of 37% and an RMSE of 497154. In terms of MAPE and RMSE, the SARIMA intervention method provides better results than the Prophet model in forecasting the number of domestic passengers at Soetta Airport.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9593covid-19 pandemicintervention modelfb prophetairline passengertime series data |
| spellingShingle | Vivin Nur Aziza Fatma Hilali Moh'd Firda Aulia Maghfiroh Khairil Anwar Notodiputro Yenni Angraini PERFORMANCE COMPARISON OF SARIMA INTERVENTION AND PROPHET MODELS FOR FORECASTING THE NUMBER OF AIRLINE PASSENGER AT SOEKARNO-HATTA INTERNATIONAL AIRPORT Barekeng covid-19 pandemic intervention model fb prophet airline passenger time series data |
| title | PERFORMANCE COMPARISON OF SARIMA INTERVENTION AND PROPHET MODELS FOR FORECASTING THE NUMBER OF AIRLINE PASSENGER AT SOEKARNO-HATTA INTERNATIONAL AIRPORT |
| title_full | PERFORMANCE COMPARISON OF SARIMA INTERVENTION AND PROPHET MODELS FOR FORECASTING THE NUMBER OF AIRLINE PASSENGER AT SOEKARNO-HATTA INTERNATIONAL AIRPORT |
| title_fullStr | PERFORMANCE COMPARISON OF SARIMA INTERVENTION AND PROPHET MODELS FOR FORECASTING THE NUMBER OF AIRLINE PASSENGER AT SOEKARNO-HATTA INTERNATIONAL AIRPORT |
| title_full_unstemmed | PERFORMANCE COMPARISON OF SARIMA INTERVENTION AND PROPHET MODELS FOR FORECASTING THE NUMBER OF AIRLINE PASSENGER AT SOEKARNO-HATTA INTERNATIONAL AIRPORT |
| title_short | PERFORMANCE COMPARISON OF SARIMA INTERVENTION AND PROPHET MODELS FOR FORECASTING THE NUMBER OF AIRLINE PASSENGER AT SOEKARNO-HATTA INTERNATIONAL AIRPORT |
| title_sort | performance comparison of sarima intervention and prophet models for forecasting the number of airline passenger at soekarno hatta international airport |
| topic | covid-19 pandemic intervention model fb prophet airline passenger time series data |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9593 |
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