Sekretariat Badan Penelitian dan Pengembangan Perhubungan
Publishing Year
2024
Publishing Place
Collation
Abstract/Notes
Ground time plays an important role in keeping flight on-time performance and passenger smooth flow. It varies depending on the aircraft type, procedures, passenger number and/or cargo amount, maintenance requirements, and ground handling service quality. This research aims to explore the ground time distribution pattern at Soekarno-Hatta International Airport. The daily flight historical data is divided into several categories based on the airline’s service type for local airlines, the airline’s origin for foreign airlines, the type of flight, and aircraft size. Ground time data of each flight category is then fitted to all possible distribution types by using the Distribution Fitting app in Matlab. The best-fitted distribution definition uses the Kolmogorov-Smirnov test by comparing the p-value of each distribution. 6 distributions fit 20 flight categories. Almost all local airlines’ ground time except full-service carrier international flights and low-cost carrier international flights with wide-body aircraft fit to Burr distribution. Full-service carrier international flight with narrow and wide-body aircraft, international flight with narrow-body aircraft operated by airlines from China and other countries fit Generalized Extreme Value distribution. Low-cost carrier international flights with wide-body aircraft and private flights fit to Inverse Gaussian distribution. International flights with wide-body aircraft operated by airlines from Korea, Japan, and other countries airlines fit for Nakagami distribution. While the cargo flights fit t Location-Scale distribution for wide-body aircraft and Weibull distribution for narrow-body aircraft. Then the stochastic models are developed based on each flight category’s distribution parameters. These models are expected to be able to guide future research in ground time or apron capacity management as they provide the data distribution without more primary data needed.
