FORECASTING ANALYSIS OF NEW STUDENTS ACCEPTANCE USING TIME SERIES FORECASTING METHOD
Keywords:
Demand forecasting, moving average, exponential smoothing, trend analysis.Abstract
New students admission (PMB) is a routine activities for education institution. Therefore, it was necessary for the institution to be aware of the mechanism of PMB to produce competent and qualified prospective students. Forecasting of PMB needed to predict the number of students and to prepare the institution infrastucture facilities to welcome the new freshmen. The research discussed the determination of forecasting number of Universitas Bina Sarana Informatika PSDKU Karawang students by using time series forecasting with three different method: moving everage, exponential smoothing and trend analysis. It also compare Mean Absolute Presentage Error (MAPE) calculated by QM for Windows. The result of the research showed that trend analysis was the most effective method which had 41.84 MAD, 2324.28 MAD, 4.99 % of MAPE and 557 students for next forecasting. The conclussion from data analysis processing showed that Universitas Bina Sarana Informatika should provide all of infrastructure facilities for the teaching and learning process with the number of 557 students in 2020.
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