Measuring the Performance of Rice Production in Kuala Nerang Region Using Grey Relational Analysis

Rice is the primary food source in majority of Asian countries. Recently, there has been a significant annual decline in rice production, not only in Malaysia but worldwide. This highlights the importance of analysing the current productivity of domestic rice, particularly in Kedah, which is popular...

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Bibliographic Details
Published in:2024 5th International Conference on Artificial Intelligence and Data Sciences, AiDAS 2024 - Proceedings
Main Author: Amin F.A.M.; Fauzi N.F.F.M.; Rodzi Z.M.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209670916&doi=10.1109%2fAiDAS63860.2024.10730225&partnerID=40&md5=b1c7f5a40171f3022eba6da5c7320767
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Summary:Rice is the primary food source in majority of Asian countries. Recently, there has been a significant annual decline in rice production, not only in Malaysia but worldwide. This highlights the importance of analysing the current productivity of domestic rice, particularly in Kedah, which is popularly known as the 'Rice Bowl of Malaysia'. The main purpose of this study is to evaluate, compare and rank the performance of 16 villages in Kuala Nerang via Grey Relational Analysis (GRA). Data was collected from 2015 to 2019 based on five important criteria: farm size, number of farmers, cost of pesticides, fertilizer and cost of machinery. The result show that Kg. Baru Tualak is the best-performing village, setting a benchmark for others. The finding also indicate that optimal use of resources is the most effective way to increase rice productivity. Overall, GRA proved to be highly effective tool for performance evaluation, even in situations of limited data availability related to the relevant criteria. Finally, this study is significant because it assists to the evaluation of Kuala Nerang rice farmers' performance through the application of the GRA model. © 2024 IEEE.
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DOI:10.1109/AiDAS63860.2024.10730225