IMPLEMENTASI SISTEM CERDAS LEAST SQUARE DALAM MERAMALKAN PEMENUHAN KEBUTUHAN STOK LISTRIK DI KOTA LHOKSEUMAWE - Muhammad Sadli; Safwandi Safwandi (Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering), 2017)
PLN (Perusahaan Listrik Negara) is one of the BUMN (Badan Usaha Milik Negara) in charge of providing electricity supply needs with the best service quality for the community. The growth of electricity demand for residents of Lhokseumawe City by 2020 is expected to increase to 10%. Based on these predictions, PLN must be able to forecast patterns from data needs lsitrik which has been then used to project the data that will come in order to give the best pelyanan for the community. Forecasting is one of the sciences in the field of intelligent systems that can predict long-term electrical demand in the city of Lhokseumawe. The least square forecasting model can be one of the components supporting the economic growth of Lhokseumawe City. Variables to be predicted in the fulfillment of electricity stocks are seen from household, industrial, commercial and public expenses. Furthermore, the need for electricity stock from each region will be seen from the installed capacity, power capable (MW) and peak load. Then the least quare forecasting model will determine the equation of data trend based on the data needs of electricity that has been then used to project the data needs of electricity to come. This research is expected to produce accurate forecasting value so that can be used as a reference for PLN party in taking policy. Proper forecasting can help PLN to save production cost due to mis-distribution. The specific target of this research is to know the quality of service PLN Lhokseumawe to the public so that the distribution of electricity is always stable. The long-term goal of implementing this smart forecasting system is to help improve the quality of PLN's services in meeting the long-term electricity needs of the people of Lhokseumawe.