Forecasting PM2.5 Concentration in Medan City Using the ARIMAX Method with Meteorological Factors as Exogenous Variables

Abstract

Particulate Matter 2.5 (PM_2.5) is a fine particle measuring less than 2.5 micrometers which is dangerous for human health because it can penetrate the respiratory system and cause cardiovascular disorders. High PM_2.5 concentrations reflect a decline in air quality, so forecasting efforts are needed to support pollution control and environmental policies. This study aims to forecast daily PM_2.5 concentrations in Medan City using the Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) method by considering meteorological factors as exogenous variables. The data used consist of PM_2.5 concentrations and average temperature, humidity, rainfall, and wind speed data for the period from June 1, 2024 to June 10, 2025. The analysis results show that the best model is ARIMAX (4,1,0) with exogenous variables of average temperature and rainfall, where temperature has a positive effect and rainfall has a negative effect on PM_2.5. This model meets the assumptions of white noise and residual normality, with a MAPE value of 20.635%, indicating a fairly good level of forecasting accuracy. The forecasting results show PM_2.5 concentrations in the range of 19–26 µg/m³ with a downward trend at the end of June 2025, indicating improved air quality in Medan City. Thus, the ARIMAX method with meteorological factors is considered effective in modeling and forecasting PM_2.5 dynamics in urban areas.