Nowcasting the Number of Airplane Passengers at Ngurah Rai Airport Using Google Trends Data
Data on the number of aircraft passengers is essential to airport managers and the government's policies. The policy relates to improving the facilities and capacity of airports and other affected sectors, such as the transportation and tourism industries. A policy taken will be better if the d...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Udayana University, Institute for Research and Community Services
2023-10-01
|
| Series: | Lontar Komputer |
| Online Access: | https://ojs.unud.ac.id/index.php/lontar/article/view/93169 |
| _version_ | 1797644985659555840 |
|---|---|
| author | I Putu Juni Adi Widianata Nori Wilantika |
| author_facet | I Putu Juni Adi Widianata Nori Wilantika |
| author_sort | I Putu Juni Adi Widianata |
| collection | DOAJ |
| description | Data on the number of aircraft passengers is essential to airport managers and the government's policies. The policy relates to improving the facilities and capacity of airports and other affected sectors, such as the transportation and tourism industries. A policy taken will be better if the data used is very close to the time of policy decision-making. Therefore, a technique is needed to forecast very close to the current condition of the number of aircraft passengers, namely nowcasting. One of the data sources that can be used for nowcasting is Google Trends data. In this study, the identification of relevant keywords used for nowcasting, the formation of nowcasting models, and the search for the best model for nowcasting the number of aircraft passengers was carried out. The nowcasting methods used are SARIMAX and multilayer perceptron. In this study, five relevant keywords were generated for domestic departures and two for international departures. In the nowcasting modeling, the best model for nowcasting domestic departures is produced, namely the multilayer perceptron with MAPE and MAE values of 11.194% and 28.048 respectively, while for departures Internationally, the best model was produced, namely SARIMAX with MAPE and MAE values of 8,641% and 50,205 respectively. |
| first_indexed | 2024-03-11T14:39:20Z |
| format | Article |
| id | doaj.art-cdc2a2feb8664c0d8fb7fed24c61330b |
| institution | Directory Open Access Journal |
| issn | 2088-1541 2541-5832 |
| language | English |
| last_indexed | 2024-03-11T14:39:20Z |
| publishDate | 2023-10-01 |
| publisher | Udayana University, Institute for Research and Community Services |
| record_format | Article |
| series | Lontar Komputer |
| spelling | doaj.art-cdc2a2feb8664c0d8fb7fed24c61330b2023-10-30T15:50:12ZengUdayana University, Institute for Research and Community ServicesLontar Komputer2088-15412541-58322023-10-01141122310.24843/LKJITI.2023.v14.i01.p0293169Nowcasting the Number of Airplane Passengers at Ngurah Rai Airport Using Google Trends DataI Putu Juni Adi Widianata0Nori WilantikaPoliteknik Statistika STISData on the number of aircraft passengers is essential to airport managers and the government's policies. The policy relates to improving the facilities and capacity of airports and other affected sectors, such as the transportation and tourism industries. A policy taken will be better if the data used is very close to the time of policy decision-making. Therefore, a technique is needed to forecast very close to the current condition of the number of aircraft passengers, namely nowcasting. One of the data sources that can be used for nowcasting is Google Trends data. In this study, the identification of relevant keywords used for nowcasting, the formation of nowcasting models, and the search for the best model for nowcasting the number of aircraft passengers was carried out. The nowcasting methods used are SARIMAX and multilayer perceptron. In this study, five relevant keywords were generated for domestic departures and two for international departures. In the nowcasting modeling, the best model for nowcasting domestic departures is produced, namely the multilayer perceptron with MAPE and MAE values of 11.194% and 28.048 respectively, while for departures Internationally, the best model was produced, namely SARIMAX with MAPE and MAE values of 8,641% and 50,205 respectively.https://ojs.unud.ac.id/index.php/lontar/article/view/93169 |
| spellingShingle | I Putu Juni Adi Widianata Nori Wilantika Nowcasting the Number of Airplane Passengers at Ngurah Rai Airport Using Google Trends Data Lontar Komputer |
| title | Nowcasting the Number of Airplane Passengers at Ngurah Rai Airport Using Google Trends Data |
| title_full | Nowcasting the Number of Airplane Passengers at Ngurah Rai Airport Using Google Trends Data |
| title_fullStr | Nowcasting the Number of Airplane Passengers at Ngurah Rai Airport Using Google Trends Data |
| title_full_unstemmed | Nowcasting the Number of Airplane Passengers at Ngurah Rai Airport Using Google Trends Data |
| title_short | Nowcasting the Number of Airplane Passengers at Ngurah Rai Airport Using Google Trends Data |
| title_sort | nowcasting the number of airplane passengers at ngurah rai airport using google trends data |
| url | https://ojs.unud.ac.id/index.php/lontar/article/view/93169 |
| work_keys_str_mv | AT iputujuniadiwidianata nowcastingthenumberofairplanepassengersatngurahraiairportusinggoogletrendsdata AT noriwilantika nowcastingthenumberofairplanepassengersatngurahraiairportusinggoogletrendsdata |