Since the SMP(System Marginal Price) is a vital factor to the market participants who intend to maximize the their profit and to the ISO(Independent System Operator) who wish to operate the electricity market in a stable sense, the short-term marginal price forecasting should be performed correctly. In an electricity market the short-term market price affects considerably the short-term trading between the market entities. Therefore, the exact forecasting of SMP can influence on the profit of market participants. This paper presents a new methodology for a day-ahead SMP forecasting using ARIMA(Autoregressive Integrated Moving Average) model based on the time-series method. And also the correction algorithm is proposed to minimize the forecasting error in order to improve the efficiency and accuracy of the SMP forecasting. To show the efficiency and effectiveness of the proposed method, the case studies are performed using historical data of SMP in 2004 published by KPX(Korea Power Exchange).