Fuzzy Time Series and Artificial Neural Network: Forecasting Exportation of Natural Rubber in Malaysia

Natural rubber is one of the most important crops in Malaysia alongside palm oil, cocoa, paddy, and pineapple. Being a tropical country, Malaysia is one of the top five exporters and producers of rubber in the world. The purpose of this study is to find the forecasted value of the actual data of th...

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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/7519d51c20c44bb0aac66fe6e97807ec
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spelling	oai:doaj.org-article:7519d51c20c44bb0aac66fe6e97807ec2021-11-06T02:22:32ZFuzzy Time Series and Artificial Neural Network: Forecasting Exportation of Natural Rubber in Malaysia2600-8793https://doaj.org/article/7519d51c20c44bb0aac66fe6e97807ec2021-03-01T00:00:00Zhttp://repeater.my/index.php/jcrinn/article/view/170https://doaj.org/toc/2600-8793 Natural rubber is one of the most important crops in Malaysia alongside palm oil, cocoa, paddy, and pineapple. Being a tropical country, Malaysia is one of the top five exporters and producers of rubber in the world. The purpose of this study is to find the forecasted value of the actual data of the number of exportations of natural rubber by using Fuzzy Time Series and Artificial Neural Network. This study is also conducted to determine the best model by making comparison between Fuzzy Time Series and Artificial Neural Network. Fuzzy Time Series has allowed to overcome a downside where the classical time series method cannot deal with forecasting problem in which values of time series are linguistic terms represented by fuzzy sets. Artificial Neural Network was introduced as one of the systematic tools of modelling which has been forecasting for about 20 years ago. The error measure that was used in this study to make comparisons were Mean Square Error, Root Mean Square Error and Mean Absolute Percentage Error. The results of this study showed that the fuzzy time series method has the smallest error value compared to artificial neural network which means it was more accurate compared to artificial neural network in forecasting exportation of natural rubber in Malaysia. 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 and Artificial Neural Network: Forecasting Exportation of Natural Rubber in Malaysia
description	Natural rubber is one of the most important crops in Malaysia alongside palm oil, cocoa, paddy, and pineapple. Being a tropical country, Malaysia is one of the top five exporters and producers of rubber in the world. The purpose of this study is to find the forecasted value of the actual data of the number of exportations of natural rubber by using Fuzzy Time Series and Artificial Neural Network. This study is also conducted to determine the best model by making comparison between Fuzzy Time Series and Artificial Neural Network. Fuzzy Time Series has allowed to overcome a downside where the classical time series method cannot deal with forecasting problem in which values of time series are linguistic terms represented by fuzzy sets. Artificial Neural Network was introduced as one of the systematic tools of modelling which has been forecasting for about 20 years ago. The error measure that was used in this study to make comparisons were Mean Square Error, Root Mean Square Error and Mean Absolute Percentage Error. The results of this study showed that the fuzzy time series method has the smallest error value compared to artificial neural network which means it was more accurate compared to artificial neural network in forecasting exportation of natural rubber in Malaysia.
format	article
title	Fuzzy Time Series and Artificial Neural Network: Forecasting Exportation of Natural Rubber in Malaysia
title_short	Fuzzy Time Series and Artificial Neural Network: Forecasting Exportation of Natural Rubber in Malaysia
title_full	Fuzzy Time Series and Artificial Neural Network: Forecasting Exportation of Natural Rubber in Malaysia
title_fullStr	Fuzzy Time Series and Artificial Neural Network: Forecasting Exportation of Natural Rubber in Malaysia
title_full_unstemmed	Fuzzy Time Series and Artificial Neural Network: Forecasting Exportation of Natural Rubber in Malaysia
title_sort	fuzzy time series and artificial neural network: forecasting exportation of natural rubber in malaysia
publisher	Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis
publishDate	2021
url	https://doaj.org/article/7519d51c20c44bb0aac66fe6e97807ec
_version_	1718443988120240128

Fuzzy Time Series and Artificial Neural Network: Forecasting Exportation of Natural Rubber in Malaysia

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