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Predictive modelling of marine fish landings in Malaysia

Rusiman, Mohd Saifullah and Sufahani, Suliadi and Mohd Robi, Nur Afifi Izzati and Abdullah, Abdul Wahab and Azmi, Nur Amira (2018) Predictive modelling of marine fish landings in Malaysia. Advances and Applications in Statistics, 53 (2). pp. 123-135. ISSN 09723617

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The fisheries sector plays an important role in the economy as a major source of food, employment and income in Malaysia. In this study, the future number of marine fish landings in Malaysia will be predicted. The monthly data from January 2005 until December 2014 were taken from Department of Fisheries Malaysia, Ministry of Agriculture and Agro-Based Industry Malaysia. The aims of this study are to predict the landing of marine fish in Malaysia by using Box-Jenkins and Holt- Winters and to make a comparison between two models in order to find the better model for prediction of marine fish landings in Malaysia. Data for the number of marine fish landings is a trend pattern. Box-Jenkins and Holt-Winters approach will be applied to the number of marine fish landings. In this study, the forecast accuracy of Box-Jenkins and Holt-Winters approach has been compared by using the mean square error (MSE) and mean absolute percentage error (MAPE). The better model obtained from Box-Jenkins approach was SARIMA(2, 1, 0)(0, 1, 1)12. For Holt-Winters, additive model is chosen since the MSE and MAPE values are lower. After comparing the Box-Jenkins approach and additive Holt-Winters, it is found that additive Holt-Winters is a better method with a lower value of MSE and MAPE and could be used by fisheries managers and scientists to decide on sustainable management issues.

Item Type: Article
Uncontrolled Keywords: Box-Jenkins; Holt-Winters; MSE; MAPE
Subjects: Q Science > QA Mathematics > QA273 Probabilities. Mathematical statistics
Divisions: Faculty of Applied Science and Technology > Department of Mathematics and Statistic
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 13 May 2019 01:13
Last Modified: 13 May 2019 01:13
URI: http://eprints.uthm.edu.my/id/eprint/11198
Statistic Details: View Download Statistic

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