FORECASTING THE NUMBER OF ADMISSION OF NEW STUDENTS OF STATE POLITECHNIC USING EXPONENTIAL SINGLE SMOOTING METHODS

Abstract

Forecasting is a prediction of uncertain events in the future. Forecasting the number of new students is one of the things that can be used for planning materials for the teaching and learning process, therefore it is necessary to predict the number of new students. This research was conducted at Malang State Polytechnic. The annual data analyzed was taken from 2011 to 2017. To predict the number of new students, the Single Exponential Smoothing method was used. This forecasting method focuses on decreasing the priority exponentially on the previous observation object. In exponential smoothing or exponential smoothing there are one or more smoothing parameters determined explicitly, and this result determines the weight imposed on the observation value. Based on the calculation results, the smallest error value is found at the value of α = 0.9 with MAD value 8.41, MAPE 7.21%, and RMSE 10.7.