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iRICE decision support system: time-series forecasting model for the risk management system


Citation

Husin, Nor Azura and Sivajiganason, Vishnuu A. L. and Kamaruzzaman, Nurul Nadhrah and Mazlan, Norida and Sitanggang, Imas Sukaesih (2024) iRICE decision support system: time-series forecasting model for the risk management system. Journal of Advanced Research in Applied Sciences and Engineering Technology, 33 (2). pp. 160-173. ISSN 2462-1943

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
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
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