Implementasi Performance Improved Holt-Winters Untuk Prediksi Jumlah Keberangkatan Domestik di Bandar Udara Soekarno Hatta - Revinda Bertananda; Budi Darma Setiawan; Marji Marji (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Air transportation in Indonesia is experiencing a rapid increase. Given the developments that occur, it's not impossible that in the future air transport will be a superior transportation again. But every flight in an airport doesn't always carry the same number of passengers each month. The number of these unconfirmed passengers should always be predictable so that the airport can determine policies to adjust the increase or decrease the number of passengers in the future. Prediction done in this research using Performance Improved Holt-Winters method. This method can predict time series data that has a data pattern with seasonal variation. In its calculations, Performance Improved Holt-Winters method involves trend and seasonality and is based on three smoothing equations: overall smoothing (level), trend smoothing, and seasonal smoothing. The data used in this study is the data of domestic departure at Soekarno Hatta airport from January 2012 to December 2017 which obtained from the official website of Central Bureau of Statistics Indonesia (www.bps.go.id). From the results of tests that have been done, the result of the smallest MAPE value is 2,976% with the parameter value Î± (alpha) = 0,04; Î² (beta) = 0,002; Î¥ (gamma) = 0,1; the number of training data = 60, and testing data = 12.