The increasing demand for electricity has driven the need for well-structured power system planning. Long-term load forecasting is one of the key elements. This paper proposes the Extreme Learning Machine (ELM) method to forecast long-term load in the Bima City Power Plant. Historical customer data and kWh sales data from PT PLN (Persero) ULP Bima from 2014 to 2020 were used to train and evaluate the ELM model. The results show that the ELM model is capable of predicting electricity load with a high level of accuracy, with a MAPE value of less than 10%. This indicates the potential of ELM as a tool to aid power system planning in Bima City
