Forecasting for Book Classified on A Library by Using Single Exponential Smoothing (case Study : Library of Bhayangkara Surabaya University) - Deddy Gita A.P; Rifki Fahrial Zainal; M Mahaputra Hidayat (JEECS (Journal of Electrical Engineering and Computer Sciences), 2017)
To facilitate the addition of library collections of UBHARA libraries, in this study will provide a solution to fieldmanuals based on forecasting using MSE single exponential smoothing formula errors and RMSE errors. Data isforecast from 2012 to 2016, with the value of each field of economics, law, socio-political, and engineering. The datawill be processed through the pre-processing process before preparing the data to be forecast. In the calculationexample, the program uses data in 2012 and 2015, alpha value = 0.1 and is calculated from month 1 to month to 3months so it is estimated to 4. The result of the data obtained is borrowed book which has the highest data isEconomy. Because in every data the number of loan books looks more dominant economic data. In 2015 thecalculation shows the value of MSE error and RMSE error. The error value to determine whether the errorforecasting results is better or not. For 2015 forecast data to be displayed at the value of the error.