Time Series Intervention Analysis With Gradual Impact Function A Case Study Of Railway Passenger Volume In Java Island - Zulhijrah, Zulhijrah; Isnaini, Mardatunnisa; Angraini, Yenni; Notodiputro, Khairil Anwar; Mualifah, Laily Nissa Atul (Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar, 2025)
Java Island has been significantly impacted by the COVID-19 pandemic, which started in March 2020. This study aims to analyze the impact of the pandemic on the volume of railway passengers’ volume with a time series approach using an interventional ARIMA model. The data used is the number of monthly passengers from 2015 to 2024. Initial modeling on data before the pandemic produced the best model, namely ARIMA (0,2,1). To measure the impact of the pandemic, a gradual step intervention function is used which represents the gradual effect of the event. The estimation results show that the ARIMA (0,2,1) model with a gradual step intervention function is able to provide more accurate forecasting results, with a MAPE value of 18.39%. This model effectively captures changes in mobility patterns due to the pandemic, especially in the post-intervention recovery phase. The findings make an important contribution to transportation policy evaluation and future strategic planningKeywords: Time Series, ARIMA Intervention, Gradual Function, Railway