<![CDATA[Air quality is an important indicator in assessing environmental conditions because it directly affects human health. The increase in industrial activities, transportation, and infrastructure development in Balikpapan City along with the development of the Nusantara Capital (IKN) has the potential to increase the concentration of air pollutants, particularly fine particulate matter PM2.5. This study aims to analyze patterns and forecast PM2.5 concentrations in Balikpapan City. This study uses the Autoregressive Integrated Moving Average (ARIMA) method to model daily PM2.5 time series data. The data used covers the period from January to September 2025 with a total of 273 observations, divided into 80% training data, which is 218 observations, and 20% testing data, which is 55 observations. The ARIMA method was chosen because of its ability to capture fluctuating patterns in time series data. The research results indicate that the ARIMA(2,0,1) model is the best model for forecasting PM2.5 concentration in Balikpapan City based on model selection criteria and forecast performance evaluation. This model is able to represent historical data patterns well and provides fairly accurate forecasting results on the test data. The conclusion of this study shows that the ARIMA(2,0,1) model can be used as an air quality forecasting tool, particularly for PM2.5 concentration in Balikpapan City, and has the potential to support policy-making in controlling air pollution in the area.]]>
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