Patient Data Set Publication through Differential Privacy via Wavelet Transforms

Abstract: This paper presents a new method of electric consumption forecasting by using time series comparison with a new method initiative used in a semiconductor plant. The source of time series data comes from the Metropolitan Electricity Authority (MEA) monthly energy consumption (kWh) during 2010 – 2012, 36 months in total and projection six months ahead compared with a new method. The objective is to select the best forecasting method from least Mean Absolute Present Error (MAPE). The results of this study show that a new method was the best method and least MAPE at 2.48 and also shows the highest significant level compared to the others by using interpolation model in Minitab and excel program. The best forecasting method will be used in forecasting the electricity consumption in the future.

Keywords; Time series method, Electric load forecasting, Mean absolute present error, Idle machine, Machine equirements