Peramalan Jumlah Penumpang Kereta Api Indonesia (Persero) Divisi Regional II Sumatera Barat Menggunakan Metode ARIMA - Tisa Revina Dewi; Helma Helma; Meira Parma Dewi (UNIVERSITAS NEGERI PADANG, 2021)
Abstract – PT. Kereta Api Indonesia (Persero) Regional Division II West Sumatera is currently facing the problem of carrying capacity that doesn’t meet the increasing passenger capacity. Therefore, will be made forecasting the number of train passengers for the future, so that the PT. Kereta Api can prepare the necessary facilities. The purpose of this study was to obtain a forecasting model and forecast the number of train passengers starting from the month of August 2015 until July 2016. The methods used are ARIMA method. After going through the stage of model identification, assessment and testing parameters, as well as the diagnostic phase, the obtained ARIMA(0,1,1)(0,1,1)12 as a suitable model for predicting the number of railway passengers with the model Yt = 243,6 + Yt-1 + Yt-12 –Yt-13 + et – 0,7689 et-1 – 0,8271 et-12 + (0,7689 x 0,8271) et-13 .Keywords – PT. Kereta Api, The Number of Passengers, Forecasting, ARIMA MethodAbstract – PT. Kereta Api Indonesia (Persero) Regional Division II West Sumatera is currently facing the problem of carrying capacity that doesn’t meet the increasing passenger capacity. Therefore, will be made forecasting the number of train passengers for the future, so that the PT. Kereta Api can prepare the necessary facilities. The purpose of this study was to obtain a forecasting model and forecast the number of train passengers starting from the month of August 2015 until July 2016. The methods used are ARIMA method. After going through the stage of model identification, assessment and testing parameters, as well as the diagnostic phase, the obtained ARIMA(0,1,1)(0,1,1)12 as a suitable model for predicting the number of railway passengers with the model Yt = 243,6 + Yt-1 + Yt-12 –Yt-13 + et – 0,7689 et-1 – 0,8271 et-12 + (0,7689 x 0,8271) et-13 . Keywords – PT. Kereta Api, The Number of Passengers, Forecasting, ARIMA Method