Modelling of palm oil export trend in Malaysia

Oil palm is one of the important export crops of Malaysia. In addition, oil palm industry contributes significantly to the country’s wellbeing by being one of the main contributors to the Gross National Product and provides employments. In this study, time series technique is used to analyse and for...

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Main Authors: Abas, Norzaida, Kamisan, Asrad, A. Halim, Syafrina
Format: Article
Language:English
Published: Penerbit Akademia Baru 2017
Subjects:
Online Access:http://eprints.utm.my/80443/1/NorzaidaAbas2017_ModellingofPalmOilExportTrend.pdf
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author Abas, Norzaida
Kamisan, Asrad
A. Halim, Syafrina
author_facet Abas, Norzaida
Kamisan, Asrad
A. Halim, Syafrina
author_sort Abas, Norzaida
collection ePrints
description Oil palm is one of the important export crops of Malaysia. In addition, oil palm industry contributes significantly to the country’s wellbeing by being one of the main contributors to the Gross National Product and provides employments. In this study, time series technique is used to analyse and forecast palm oil exports of Malaysia. While various studies are available on modelling of palm oil, very few studies are found focusing on the modelling of palm oil exports. Model based on multiplicative decomposition method is employed to analyse the monthly exports. Time series data from January 2012 to April 2017 are transformed through a series of procedures to decompose the data into seasonal and trend components. Subsequently, the constructed model is used to make forecasting of future export for several months. Results show that the model is able to replicate the pattern of the observed data. A slight negative trend is detected for the export values. The overall forecasted export values show there is some small fluctuation between the months.
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spelling utm.eprints-804432019-05-22T06:45:03Z http://eprints.utm.my/80443/ Modelling of palm oil export trend in Malaysia Abas, Norzaida Kamisan, Asrad A. Halim, Syafrina TP Chemical technology Oil palm is one of the important export crops of Malaysia. In addition, oil palm industry contributes significantly to the country’s wellbeing by being one of the main contributors to the Gross National Product and provides employments. In this study, time series technique is used to analyse and forecast palm oil exports of Malaysia. While various studies are available on modelling of palm oil, very few studies are found focusing on the modelling of palm oil exports. Model based on multiplicative decomposition method is employed to analyse the monthly exports. Time series data from January 2012 to April 2017 are transformed through a series of procedures to decompose the data into seasonal and trend components. Subsequently, the constructed model is used to make forecasting of future export for several months. Results show that the model is able to replicate the pattern of the observed data. A slight negative trend is detected for the export values. The overall forecasted export values show there is some small fluctuation between the months. Penerbit Akademia Baru 2017 Article PeerReviewed application/pdf en http://eprints.utm.my/80443/1/NorzaidaAbas2017_ModellingofPalmOilExportTrend.pdf Abas, Norzaida and Kamisan, Asrad and A. Halim, Syafrina (2017) Modelling of palm oil export trend in Malaysia. Journal of Advanced Research in Business and Management Studies, 8 (2). pp. 7-11. ISSN 2462-1935 http://www.akademiabaru.com/doc/ARBMSV8_N2_P7_11.pdf
spellingShingle TP Chemical technology
Abas, Norzaida
Kamisan, Asrad
A. Halim, Syafrina
Modelling of palm oil export trend in Malaysia
title Modelling of palm oil export trend in Malaysia
title_full Modelling of palm oil export trend in Malaysia
title_fullStr Modelling of palm oil export trend in Malaysia
title_full_unstemmed Modelling of palm oil export trend in Malaysia
title_short Modelling of palm oil export trend in Malaysia
title_sort modelling of palm oil export trend in malaysia
topic TP Chemical technology
url http://eprints.utm.my/80443/1/NorzaidaAbas2017_ModellingofPalmOilExportTrend.pdf
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