Penerapan Long Short Term Memory untuk Memprediksi Flight Delay pada Penerbangan Komersial - Muhammad Genta Ari Shandi; Rifki Adhitama; Amalia Beladinna Arifa (Ikatan Ahli Informatika Indonesia (IAII), 2020)
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.