Forecasting modelling of cockles in Malaysia by using time series analysis

Ngali, Zamani and Jemain, Noratika Budi and Chang, An Wee and Abdol Rahman, Mohd Nasrull and Kaharuddin, Muhammad Zulhilmi and Khairu Razak, Siti Badriah (2018) Forecasting modelling of cockles in Malaysia by using time series analysis. International Journal of Engineering & Technology, 7 (4.3). pp. 488-491. ISSN 2227-524X

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Cockle farmed in Malaysia are from Anadara genes and Arcidae family which known as blood cockle. Normally, it was found in the farmed around mangrove estuary areas in the muddy and sandy shores. This study aims to predict the production of cockle to ensure sure the cockle supplies are synchronised with the demand. Then, based on the demand, the prediction result could be used to make decision either to import or export the cockle. The data were taken from the Department of Fisheries Malaysia (DFM) and it has cyclic pattern data. There are two methods used in this study which are Holt-Linear method and Auto regressive moving average (ARMA). In determining the best fitted model between the two methods, the mean square error (MSE) values will be compared and the lowest value of MSE will assign as the best model. Result shows that ARMA(1,1) is the best model compared to Holt-Linear. Therefore, ARMA(1,1) model will be used to forecast the production of cockle in Malaysia.

Item Type: Article
Uncontrolled Keywords: Auto regressive moving average (ARMA); Holt-Linear; Mean Square Error (MSE)
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Q Science > QA Mathematics > QA299.6-433 Analysis
T Technology > TA Engineering (General). Civil engineering (General) > TA329-348 Engineering mathematics. Engineering analysis
Divisions: Faculty of Applied Science and Technology > Department of Mathematics and Statistics
Depositing User: UiTM Student Praktikal
Date Deposited: 06 Jan 2022 01:48
Last Modified: 06 Jan 2022 01:48

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