Passenger volume forecasting information system for PT. KAI Daop 2 Bandung using double exponential smoothing method

Abstract

Daop 2 Bandung is one of the Indonesian railroad operations areas, under the administration of PT Kereta Api Indonesia (Persero). Daop 2 Bandung is currently experiencing a problem in predicting the number of passenger volumes. It is common for railway transportation services to experience passengers flows that increases or decreases in the volume which in turn causes the service of the PT. KAI becomes less optimum. Therefore, a forecasting information system is needed to forecast the volume of train passengers in the upcoming period. This study applied Double Exponential Smoothing method as a forecasting method. The data used is the number of passenger volume data for two periods, i.e. 2017 and 2018 periods. For forecasting accuracy, PE (Percentage Error) and MAPE (Mean Absolute Percentage Error) were used. The passenger volume forecasting results on the Executive Class category shows 946,824 with an error percentage of 11.9962%, the Business Class category shows 221,188 results with an error percentage of 21.6714%, and the Economy Class category shows 5,144,074 with an error percentage of 10.4366%.