Forecasting Dropout Trend at King’s College of The Philippines using ARI-MA Modeling
DOI:
https://doi.org/10.11594/ijmaber.04.06.32Keywords:
ARIMA, Differencing, ForecastAbstract
Student drop-outs continue to be one of the perineal problems of educational institutions. Accordingly, institution managers are trying to find ways and means to curb impending issues on drop-outs to satisfy quality education. In this paper, the researcher delved into the different time series modeling methods in order to forecast the rate of college dropouts at King’s College of the Philippines-Benguet. The method considered was the Autoregressive Integrated Moving Average (ARIMA) model. The data used in this paper was the number of school dropouts from 2005 to 2018 obtained from the school registrar which shows more dropout during the first semester than the second semester. Initial result obtained from using ARIMA reveals that the best model used is the model ARIMA which is the auto regression (AR 1), then the moving average (MA 1), with first differencing on the second semester.
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