CD Skripsi
Prediksi Tingkatan Penggunaan Transportasi Massal Masyarakat Indonesia Menggunakan Metode Arima
Mass transportation plays an important role in community mobility in Indonesia. Therefore, predicting the level of use of mass transportation is crucial in planning and policy making. This study aims to forecast the number of mass transportation users in Indonesia using the Autoregressive Integrated Moving Average (ARIMA) method. The results of this study show that the ARIMA (1,1,0) model on aircraft data provides better predictive value results compared to the other two models, namely the ARIMA (0,1,1) model and the ARIMA (2,1,0) model. The ARIMA (1,1,0) model has been successfully tested significant with a p-value of 0,0635 smaller than the alpha value of 0,10 accompanied by the lowest Akaike Information Criterion (AIC) value of 1368,6275 and evaluation of model accuracy measurement using Root Mean Square Error (RMSE) of 669.218. And in the train data, the ARIMA (0,1,0) model provides the best predictive value results compared to the other two models, namely the ARIMA (0,1,1) model and the ARIMA (1,1,0) model. The ARIMA (0,1,0) model has been successfully tested significant with a p-value of 0,0001745 smaller than the alpha value of 0,05 accompanied by the lowest Akaike Information Criterion (AIC) value of 1489,44 and evaluation of model accuracy measurement using Root Mean Square Error (RMSE) which is 2.542.836.
Keywords: ARIMA, Plane, Prediction, Train, Transportation
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