Application of The Least Square Method for The Prediction of The Number of Registration in Admission of New Students in Universities
Keywords:forecasting, Least Square method
Seeing the huge potential that can be explored in new student admissions, the authors are interested in looking for stored patterns from the data to get predictions and information. That is to predict the number of registrants in the following year. To solve these problems, a method is used, namely the least square method. The existing data are five time series, consisting of five years of new student admissions data. To calculate the error rate, the mean absolute deviation (MAD), the mean square error (MSE), and the mean absolute percentage error (MAPE) are used. With the prediction results for 2020 obtained, there are 225 people for Informatics Engineering, 82 people for Information Systems, and 11.2 people for Information Management. And the results of the measurement of the suitability of forecasting with these methods are, for Informatics Engineering as much as 0.79%, Information Systems 0.8%, and Information Management as much as 3.4%.
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