Fuzzy Time Series for Projecting School Enrolment in Malaysia

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...

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Formato:	article
Lenguaje:	EN
Publicado:	Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis 2021
Materias:	Probabilities. Mathematical statistics QA273-280 Technology T Technology (General) T1-995
Acceso en línea:	https://doaj.org/article/c0a2e8d4d2fe453dbe79920a945a94d2
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spelling	oai:doaj.org-article:c0a2e8d4d2fe453dbe79920a945a94d22021-11-06T02:22:07ZFuzzy Time Series for Projecting School Enrolment in Malaysia2600-8793https://doaj.org/article/c0a2e8d4d2fe453dbe79920a945a94d22021-03-01T00:00:00Zhttp://repeater.my/index.php/jcrinn/article/view/180https://doaj.org/toc/2600-8793 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 are 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. Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA PerlisarticleProbabilities. Mathematical statisticsQA273-280TechnologyTTechnology (General)T1-995ENJournal of Computing Research and Innovation, Vol 6, Iss 1 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Probabilities. Mathematical statistics QA273-280 Technology T Technology (General) T1-995
spellingShingle	Probabilities. Mathematical statistics QA273-280 Technology T Technology (General) T1-995 Fuzzy Time Series for Projecting School Enrolment in Malaysia
description	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 are 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.
format	article
title	Fuzzy Time Series for Projecting School Enrolment in Malaysia
title_short	Fuzzy Time Series for Projecting School Enrolment in Malaysia
title_full	Fuzzy Time Series for Projecting School Enrolment in Malaysia
title_fullStr	Fuzzy Time Series for Projecting School Enrolment in Malaysia
title_full_unstemmed	Fuzzy Time Series for Projecting School Enrolment in Malaysia
title_sort	fuzzy time series for projecting school enrolment in malaysia
publisher	Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis
publishDate	2021
url	https://doaj.org/article/c0a2e8d4d2fe453dbe79920a945a94d2
_version_	1718444005462638592

Fuzzy Time Series for Projecting School Enrolment in Malaysia

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