Open AccessDevelopment of Automated Flight Data Collection System for Air Transportation Statistics
Author(s) -
Satria Bagus Panuntun,
Setia Pramana
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1863/1/012020
Subject(s) - python (programming language) , transport engineering , aviation , computer science , tourism , big data , real time data , statistics , operations research , geography , engineering , data mining , world wide web , mathematics , archaeology , aerospace engineering , operating system
Data and information regarding air transportation is very crucial for all aspects, such as economy, people mobility and tourism. Currently, the Air Transportation Statistics is based on administrative data of different institutions. it is necessary to have a new data source regarding air transportation activities that can be used as an alternative reference for air transportation data which is faster and more granular. This research aims to study a new approach to produce air transportation statistics, especially air transportation statistics in Indonesia from big data that can be used as comparative or as complementary data for official air transportation statistics. This research using a website scraping method from a site that provides monitoring and tracking services for all flights in the world. The flight data was collected daily from the 15 busiest airports in Indonesia for both departure and arrival flights using the API provided by the website. The Scrapy module in the Python programming language is implemented. The data was collected daily from March 15, 2020, to August 31, 2020. The results of the flight data set contain information about the flight code, aircraft code, airline name, departure airport, departure city, arrival airport, arrival city, date/time of departure and arrival, and flight status. The result shows that it is feasible to use big data as a comparative or as a complementary of official statistics, especially in air transportation statistics. By using the web scraping technique, the indicator that usually requires more time and cost can be done in real-time and less cost. This new approach is expected to improve the quality of official air transportation statistics.