FLIGHT STATUS PREDICTION

• Main Author: Mohamad Aizad, Radi
• Format: Final Year Project Report
• Language: English; English
• Published: Universiti Malaysia Sarawak, (UNIMAS) 2023
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://ir.unimas.my/id/eprint/44167/1/Mohamad%20Aizad%20%20%2824%20pgs%29.pdf; http://ir.unimas.my/id/eprint/44167/2/Mohamad%20Aizad%20%20ft.pdf; http://ir.unimas.my/id/eprint/44167/

Air travel is one of the most widely used forms of transportation around the world, including in Malaysia. It originated in 1903 with the creation and first flight of the Wright Flyer by the Wright brothers. According to statistics, the number of flights worldwide is expected to reach up to 32.4 million. Although air travel is generally more expensive compared to other modes of transportation, it remains widely used due to its speed in reaching destinations. However, a common occurrence in the airline industry is flight delays or cancellations. Factors that can lead to these disruptions include staff shortages, adverse weather conditions, and technical problems with the aircraft. Such situations can leave passengers frustrated and disappointed, particularly when their travel plans are unexpectedly affected. Therefore, this project aims to predict flight statuses using a Machine Learning approach. Comparative studies will be conducted to evaluate and compare similar projects undertaken by other