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All Journal International Journal of Advanced Science Computing and Engineering
Maliberan, Esmael V.
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Forecasting Enrolment Data of Surigao del Sur State University, Philippines using Regression Analysis and Multiplicative Decomposition Model Maliberan, Esmael V.
International Journal of Advanced Science Computing and Engineering Vol. 3 No. 1 (2021)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (309.202 KB) | DOI: 10.62527/ijasce.3.1.26

Abstract

The study endeavored to predict the number of students who will enroll in Surigao del Sur State University using the historic data from 2010-2015. It was accomplished to utilize two existing methods to form its model in forecasting the enrolment data of the University. To project the number of students enrolled at the university, regression analysis, and a multiplicative decomposition model is used. The Mean Absolute Percentage Error (MAPE) of the forecasted enrolment data was 3.10 percent, according to the results. This only demonstrated that the estimated data were similar to the actual data, implying that it is accurate. The predicted enrolment data can be used to support decision-making and as an input to the University Development Plan.
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