Introduction: The development of the Jogja Solo railway transportation, one of which is the electrification of the railway line. This electrification will increase the capacity of the number of passengers because it can cut travel time so that there will be more and more trips. The government's plan to extend the electrification of the KRL line to Kulonprogo and Madiun is an opportunity for growth in the number of Jogja Solo KRL passengers. This study aims to find the best forecasting model for the number of KRL Jogja Solo passengers among short-term forecasting models. Methods: The forecasting method used is the Gray Method (1.1), Moving Average and Exponential Smoothing. Furthermore, based on the forecasting results of each method, the error rate will be sought based on the MAPE, MAD and MSD values. Result: The error prediction value among the three selected methods, namely Gray (1,1), second-order moving average and single exponential smoothing, the results obtained from the single exponential smoothing method have the slightest error value compared to the others. So this method is the best method chosen to predict the number of Jogja Solo KRL passengers. Conclusion: the single exponential smoothing method is the best forecasting method because it has the mirror value, namely MAPE of 51, MAD of 50,308 and MSD of 3,891,632,651. The prediction results for the 14th-period passengers obtained a result of 202,067 people. The prediction results for the 14th-period passengers obtained a result of 202,067 people.
Pengembangan transportasi perkeretaapian Jogja Solo, salah satunya dilakukan elektrifikasi jalur perkeretaapian. Elektrifikasi ini akan meningkatkan kapasitas jumlah penumpang karena dapat memangkas waktu tempuh sehingga perjalanan semakin bertambah banyak. Rencana pemerintah untuk memperpanjang elektrifikasi jalur KRL sampai Kulonprogo dan Madiun menjadi suatu peluang pertumbuhan jumlah penumpang KRL Jogja Solo.
Penelitian ini bertujuan untuk mencari model peramalan jumlah penumpang KRL Jogja Solo terbaik diantara model peramalan jangka pendek. Metode peramalan yang digunakan adalah Metode Grey (1,1), Moving Average dan Exponential Smoothing. Selanjutnya berdasarkan hasil peramalan masing-masing metode akan dicari tingkat kesalahannya berdasarkan nilai MAPE, MAD dan MSD.
Hasil perbandingan menunjukkan metode single exponential smoothing merupakan model terbaik dengan nilai kesalalahan paling rendah yaitu MAPE sebesar 51, MAD sebesar 50.308 dan MSD sebesar 3.891.632.651. Hasil prediksi penumpang periode ke 14 diperoleh hasil sebesar 202.067 orang