The increasing energy demand in Indonesia encourages the utilization of new and renewable energy, especially solar energy. However, one of the main challenges in developing Solar Power Plants (PLTS) lies in the uncertainty caused by solar irradiance fluctuations. This research aims to develop a forecasting model using the Seasonal Autoregressive Integrated Moving Average (SARIMA) method to accurately predict solar irradiance and support the optimization of PLTS power output. Five years of historical irradiance data were collected from the PLTS system at Institut Teknologi PLN. The analysis was carried out using RStudio software for modeling and PVsyst for output simulation. The model’s accuracy was evaluated using the MAPE criterion. The results of this study are expected to provide an accurate forecasting solution for solar energy management and to support the achievement of the national renewable energy mix target