Forecasting natural rubber production in Malaysia: box-jenkins vs artificial neural network method / Liyana Husna Shamsudin and Nur Fadhliana Ithnin

The present study aims as applying different methods for forecasting the production of natural rubber in Malaysia. Two different methods, Box-Jenkins and Artificial Neural Network, were used to forecast the production of rubber. The monthly data from 1984 until 2017 were the data used to analyse and...

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Main Authors:	Shamsudin, Liyana Husna, Ithnin, Nur Fadhliana
Format:	Thesis
Language:	English
Published:	2018
Subjects:	H Social Sciences (General)
Online Access:	https://ir.uitm.edu.my/id/eprint/32569/1/32569.pdf
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id	my-uitm-ir.32569
record_format	uketd_dc
spelling	my-uitm-ir.325692020-07-16T07:07:39Z Forecasting natural rubber production in Malaysia: box-jenkins vs artificial neural network method / Liyana Husna Shamsudin and Nur Fadhliana Ithnin 2018-06 Shamsudin, Liyana Husna Ithnin, Nur Fadhliana H Social Sciences (General) Study and teaching. Research The present study aims as applying different methods for forecasting the production of natural rubber in Malaysia. Two different methods, Box-Jenkins and Artificial Neural Network, were used to forecast the production of rubber. The monthly data from 1984 until 2017 were the data used to analyse and the data split into two part which is 1984-2016 is for fit the model and 2017 for validate the model. SARIMA (0,1,2) (0,1,2)12 is the best model for Box-Jenkins analysis while Multilayer Neural Network that contain 12 input nodes, 8 hidden nodes and 1 output nodes is the best model for Artificial Neural Network analysis. The performances of the models were compared and the result shows that Artificial Neural Network model was found to model the production better since it has the lowest MAPE value. Thus, Artificial Neural Network can be an effective tool for forecasting the production of natural rubber in Malaysia 2018-06 Thesis https://ir.uitm.edu.my/id/eprint/32569/ https://ir.uitm.edu.my/id/eprint/32569/1/32569.pdf text en public degree Universiti Teknologi MARA Cawangan Kelantan Faculty of Computer and Mathematical Sciences Abd Razak, Nor Fatihah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Abd Razak, Nor Fatihah
topic	H Social Sciences (General) H Social Sciences (General)
spellingShingle	H Social Sciences (General) H Social Sciences (General) Shamsudin, Liyana Husna Ithnin, Nur Fadhliana Forecasting natural rubber production in Malaysia: box-jenkins vs artificial neural network method / Liyana Husna Shamsudin and Nur Fadhliana Ithnin
description	The present study aims as applying different methods for forecasting the production of natural rubber in Malaysia. Two different methods, Box-Jenkins and Artificial Neural Network, were used to forecast the production of rubber. The monthly data from 1984 until 2017 were the data used to analyse and the data split into two part which is 1984-2016 is for fit the model and 2017 for validate the model. SARIMA (0,1,2) (0,1,2)12 is the best model for Box-Jenkins analysis while Multilayer Neural Network that contain 12 input nodes, 8 hidden nodes and 1 output nodes is the best model for Artificial Neural Network analysis. The performances of the models were compared and the result shows that Artificial Neural Network model was found to model the production better since it has the lowest MAPE value. Thus, Artificial Neural Network can be an effective tool for forecasting the production of natural rubber in Malaysia
format	Thesis
qualification_level	Bachelor degree
author	Shamsudin, Liyana Husna Ithnin, Nur Fadhliana
author_facet	Shamsudin, Liyana Husna Ithnin, Nur Fadhliana
author_sort	Shamsudin, Liyana Husna
title	Forecasting natural rubber production in Malaysia: box-jenkins vs artificial neural network method / Liyana Husna Shamsudin and Nur Fadhliana Ithnin
title_short	Forecasting natural rubber production in Malaysia: box-jenkins vs artificial neural network method / Liyana Husna Shamsudin and Nur Fadhliana Ithnin
title_full	Forecasting natural rubber production in Malaysia: box-jenkins vs artificial neural network method / Liyana Husna Shamsudin and Nur Fadhliana Ithnin
title_fullStr	Forecasting natural rubber production in Malaysia: box-jenkins vs artificial neural network method / Liyana Husna Shamsudin and Nur Fadhliana Ithnin
title_full_unstemmed	Forecasting natural rubber production in Malaysia: box-jenkins vs artificial neural network method / Liyana Husna Shamsudin and Nur Fadhliana Ithnin
title_sort	forecasting natural rubber production in malaysia: box-jenkins vs artificial neural network method / liyana husna shamsudin and nur fadhliana ithnin
granting_institution	Universiti Teknologi MARA Cawangan Kelantan
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2018
url	https://ir.uitm.edu.my/id/eprint/32569/1/32569.pdf
_version_	1783734175569805312

Forecasting natural rubber production in Malaysia: box-jenkins vs artificial neural network method / Liyana Husna Shamsudin and Nur Fadhliana Ithnin

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