PEMODELAN REGRESI NONPARAMETRIK MENGGUNAKAN PENDEKATAN POLINOMIAL LOKAL PADA BEBAN LISTRIK DI KOTA SEMARANG - Suparti, Suparti; Prahutama, Alan (Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, 2016)
Semarang is the provincial capital of Central Java, with infrastructure and economicâ€™s growth was high. The phenomenon of power outages that occurred in Semarang, certainly disrupted economic development in Semarang. Large electrical energy consumed by industrial-scale consumers and households in the San Francisco area, monitored or recorded automatically and presented into a historical data load power consumption. Therefore, this study modeling the load power consumption at a time when not influenced by the use of electrical load (t-1)-th. Modeling using nonparametric regression approach with Local polynomial. In this study, the kernel used is a Gaussian kernel. In local polynomial modeling, determined optimum bandwidth. One of the optimum bandwidth determination using the Generalized Cross Validation (GCV). GCV values obtained amounted to 1425.726 with a minimum bandwidth of 394. Modelling generate local polynomial of order 2 with MSE value of 1408.672.Â Keywords: electrical load, local polinomial, gaussian kernel, GCV.