Forecasting fresh water and marine fish production in Malaysia using ARIMA and ARFIMA models / Pauline Mah Jin Wee … [et al.]

Mah, Pauline Jin Wee and Zali, N. N. M. and Ihwal, N. A. M. and Azizan, N. Z. (2018) Forecasting fresh water and marine fish production in Malaysia using ARIMA and ARFIMA models / Pauline Mah Jin Wee … [et al.]. Malaysian Journal of Computing (MJoC), 3 (2). pp. 81-92. ISSN 2600-8238

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Malaysia is surrounded by sea, rivers and lakes which provide natural sources of fish for human consumption. Hence, fish is one source of protein supply to the country and fishery is a sub-sector that contribute to the national gross domestic product. Since fish forecasting is crucial in fisheries management for managers and scientists, time series modelling can be one useful tool. Time series modelling have been used in many fields of studies including the fields of fisheries. In a previous research, the ARIMA and ARFIMA models were used to model marine fish production in Malaysia and the ARFIMA model emerged to be a better forecast model. In this study, we consider fitting the ARIMA and ARFIMA to both the marine and freshwater fish production in Malaysia. The process of model fitting was done using the “ITSM 2000, version 7.0” software. The performance of the models were evaluated using the mean absolute error, root mean square error and mean absolute percentage error. It was found in this study that the selection of the best fit model depends on the forecast accuracy measures used.


Item Type: Article
Email / ID Num.
Mah, Pauline Jin Wee
Zali, N. N. M.
Ihwal, N. A. M.
Azizan, N. Z.
Subjects: Q Science > QA Mathematics > Mathematical statistics. Probabilities
Q Science > QA Mathematics > Evolutionary programming (Computer science). Genetic algorithms
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Journal or Publication Title: Malaysian Journal of Computing (MJoC)
UiTM Journal Collections: UiTM Journal > Malaysian Journal of Computing (MJoC)
ISSN: 2600-8238
Volume: 3
Number: 2
Page Range: pp. 81-92
Keywords: Fresh water fish, Marine fish, Time series modelling, ARIMA models
Date: 2018
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