Citation
Abstract
The development of a decision support system (DSS) called the Risk Management System aims to empower farmers in making well-informed decisions, ultimately enhancing rice field production. This system focuses on providing a monitoring mechanism that optimizes monitoring and control efforts in paddy plantations. By employing predictive modeling, integrated pest monitoring, and decision support systems for pests, weeds, abiotic variables, and rainfall patterns, it predicts the likelihood and consequences of potential weed infestations, pest outbreaks, and changes in weather patterns like temperature and rainfall. By leveraging precision agriculture technologies and data-driven insights, the Risk Management System keeps a vigilant watch on disease and pest presence in paddy fields. It promptly alerts farmers when specific thresholds are surpassed, enabling them to take immediate action. The system facilitates effective data analysis for extension officers, enabling them to swiftly respond to emergency situations. Overall, this method offers a practical and efficient response to the challenges faced by paddy farmers. It equips them with the ability to make informed decisions, increase production, and effectively manage diseases and pests, ultimately leading to improved agricultural outcomes.
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Computer Science and Information Technology |
DOI Number: | https://doi.org/10.37934/araset.33.2.160173 |
Publisher: | Semarak Ilmu Publishing |
Keywords: | Abiotic factors; Decision support system; Disease and pest; Forecasting model; Paddy plantation; Predictive modeling; Risk management system; Weed infestations; Pest outbreaks; Weather patterns; Agricultural practices; Rice field production; Agricultural |
Depositing User: | Mr. Mohamad Syahrul Nizam Md Ishak |
Date Deposited: | 05 Apr 2024 03:33 |
Last Modified: | 05 Apr 2024 03:33 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.37934/araset.33.2.160173 |
URI: | http://psasir.upm.edu.my/id/eprint/105821 |
Statistic Details: | View Download Statistic |
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