期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2019
卷号：17
期号：2
页码：1023-1031
DOI：10.12928/telkomnika.v17i2.8460
出版社：Universitas Ahmad Dahlan
摘要：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%.
其他摘要：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%.
