Application of Long Short Term Memory to Predict Flight Delay on Commercial Flights

Penerapan Long Short Term Memory untuk Memprediksi Flight Delay pada Penerbangan Komersial

Authors

  • Muhammad Genta Ari Shandi IT Telkom Purwokerto
  • Rifki Adhitama Institut Teknologi Telkom Purwokerto
  • Amalia Beladinna Arifa Institut Teknologi Telkom Purwokerto

DOI:

https://doi.org/10.29207/resti.v4i3.1759

Keywords:

Departure delay, Flight, Long short term memory, Model, Recurrent neural network

Abstract

Delay in airline services, become an unpleasant experience for passengers who experience it. This study aims to build a model that can predict flight delay (departure) using the Long Short Term Memory method and can find out its performance. In this study there are two scenarios that have different ways of preprocessing. Both of these scenarios produce predictions with error values calculated using Root Mean Squared Error (RMSE), respectively from the first to the second scenario namely: 41, 21. Between the two, the second scenario is better than the first scenario due to extreme data deletion ( anomaly) in the second scenario with an error value using RMSE of 0.116.

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References

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Published

2020-06-20

Issue

Section

Computer Science Applications

How to Cite

Ari Shandi, M. G., Rifki Adhitama, & Amalia Beladinna Arifa. (2020). Application of Long Short Term Memory to Predict Flight Delay on Commercial Flights: Penerapan Long Short Term Memory untuk Memprediksi Flight Delay pada Penerbangan Komersial. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 4(3), 447-453. https://doi.org/10.29207/resti.v4i3.1759