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

  • Muhammad Genta Ari Shandi IT Telkom Purwokerto
  • Rifki Adhitama Institut Teknologi Telkom Purwokerto
  • Amalia Beladinna Arifa Institut Teknologi Telkom Purwokerto
Keywords: Departure delay, Flight, Long short term memory, Model, Recurrent neural network


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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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. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 4(3), 447 - 453.
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