Forecasting of Electric Consumption in a Semiconductor Plant using Time Series Methods

Abstract

This paper presents the method of electric consumption forecasting by using time series in analyzing data. The source of time series data come from the Metropolitan Electricity Authority (MEA) monthly energy consumption (kWh) during 2010 – 2012, 36 months in total. The objective is to select the best forecasting method from least Mean Absolute Present Error (MAPE). The results of this study show that single exponential smoothing was the best method and least MAPE at 5.60 smoothing constant  ? =   0.706780 and also shows the highest significant level compared to the others by using interpolation model in Minitab program. The best forecasting method will be used in forecasting the electricity consumption in the future.

Keywords: time series method, electric consumption forecasting, means absolute present error, energy consumption charge