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Fuzzy time series for projecting school enrolment in Malaysia
Nor Hayati Shafii1, Rohana Alias2, Siti Rohani Shamsudin3, Diana Sirmayunie Md Nasir4.
There are a variety of approaches to the problem of predicting educational enrolment. However, none of
them can be used when the historical data are linguistic values. Fuzzy time series is an efficient and
effective tool to deal with such problems. In this paper, the forecast of the enrolment of pre-primary,
primary, secondary, and tertiary schools in Malaysia is carried out using fuzzy time series approaches. A
fuzzy time series model is developed using historical dataset collected from the United Nations Educational,
Scientific, and Cultural Organization (UNESCO) from the year 1981 to 2018. A complete procedure is
proposed which includes: fuzzifying the historical dataset, developing a fuzzy time series model, and
calculating and interpreting the outputs. The accuracy of the model is also examined to evaluate how good
the developed forecasting model is. It is tested based on the value of the mean squared error (MSE), Mean
Absolute Percent Error (MAPE) and Mean Absolute Deviation (MAD). The lower the value of error
measure, the higher the accuracy of the model. The result shows that fuzzy time series model developed
for primary school enrollments is the most accurate with the lowest error measure, with the MSE value
being 0.38, MAPE 0.43 and MAD 0.43 respectively.
Affiliation:
- Universiti Teknologi MARA, Perlis Branch, Arau Campus, 02600 Arau, Perlis, Malaysia
- Universiti Teknologi MARA, Perlis Branch, Arau Campus, 02600 Arau, Perlis, Malaysia
- Universiti Teknologi MARA, Perlis Branch, Arau Campus, 02600 Arau, Perlis, Malaysia
- Universiti Teknologi MARA, Perlis Branch, Arau Campus, 02600 Arau, Perlis, Malaysia
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