The step construction of penalized spline in electrical power load data

Rezzy Eko Caraka, Sakhinah Abu Bakar, Gangga Anuraga, M A Mauludin, Anwardi Anwardi, Suwito Pormalingo, Vidila Rosalina


Electricity is one of the most pressing needs for human life. Electricity is required not only for lighting but also to carry out activities of daily life related to activities Social and economic community. The problems is currently a limited supply of electricity resulting in an energy crisis. Electrical power is not storable therefore it is a vital need to make a good electricity demand forecast. According to this, we conducted an analysis based on power load. Given a baseline to this research, we applied penalized splines (P-splines) which led to a powerful and applicable smoothing technique. In this paper, we revealed penalized spline degree 1 (linear) with 8 knots is the best model since it has the lowest GCV (Generelized Cross Validation). This model have become a compelling model to predict electric power load evidenced by of Mean Absolute Percentage Error (MAPE=0.013) less than 10%


forecasting; knot; penalized spline; non-parametric



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