Prediction model for marine shrimp production in Brunei Darussalam

Aquaculture is one of the ever-growing food-producing sectors and it is also one of the non-oil and gas industries that is contributing to Brunei Darussalam gross domestic product. This paper presents the prediction of the marine shrimp production in the aquaculture sector of Brunei Darussalam. The...

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Bibliographic Details
Main Authors: Siau, Nor Zainah, Azri, Mohammad Najwan Muhammad, Bramantoro, Arif, Suhaili, Wida Susanty
Format: Conference Proceeding
Language:English
Subjects:
Aquaculture
Fisheries
Performance measurement
Prediction models
Recurrent neural networks
Shrimps
Time series
Online Access:Get full text
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Summary:Aquaculture is one of the ever-growing food-producing sectors and it is also one of the non-oil and gas industries that is contributing to Brunei Darussalam gross domestic product. This paper presents the prediction of the marine shrimp production in the aquaculture sector of Brunei Darussalam. The study is based on data collected through primary interviews with Department of Fisheries staff and secondary data of marine shrimp production from 2010 to 2021. Several prediction techniques were used to generate highly accurate forecasts, capturing the seasonal and trend patterns found in time-series data. The Recurrent Neural Network, Linear Regression, and Random Forest were experimented, and their performances were compared. The result shows that the random forest model outperformed other time series models in predicting the production of marine shrimp in Brunei based on the major votes on its performance metrics.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0179771