**4. Prediction of Electricity Load**

As discussed in the previous section, we have investigated correlations between various weather parameters with the electricity load in Bali. The three most correlated weather parameters, i.e., 2 m temperature, net solar radiation, and wind speed, with CC values varying from −0.40 to 0.63. Three other parameters have lower CC values. This section explores possible designs for feature input of a machine-learning-based model for the electricity load forecasting system. Firstly, we investigate which weather parameters will give the best configuration for feature input for machine learning models. Secondly, we also investigate scenarios to improve prediction results by adding moving average information as an additional input for machine learning prediction.
