MECHANIZATION IN MALAYSIAN AGRICULTURE: A SYSTEMATIC REVIEW OF PRODUCTIVITY, SUSTAINABILITY, AND SOCIO-ECONOMIC PERSPECTIVES

Authors

  • Mohamad Ezral Faculty of Mechanical Engineering & Technology Engineering, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Mohd Sazli Faculty of Mechanical Engineering & Technology Engineering, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Mohd Zakimi Faculty of Mechanical Engineering & Technology Engineering, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Azuwir Mohd Nor Faculty of Mechanical Engineering & Technology Engineering, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Ahmad Fadzil Mustafa Wide Agro Venture Sdn Bhd, No 435A, Persiaran SIBC 18, Seri Iskandar Business Centre, 32610 Seri Iskandar, Perak

DOI:

https://doi.org/10.11113/jm.v49.713

Keywords:

agriculture, automation, mechanization, smart farming, systematic literature review

Abstract

Mechanisation is in fact much needed by Malaysia’s agricultural sector that has been dealing with the issues of food security, labour shortage and environmental sustainability. Recent technologies advanced, especially in IoT (Internet of Things), AI (Artificial Intelligence) and Automation provide new revolution to improve productivity and operational efficiency. Nonetheless, the contribution of these technologies to sustainable agricultural development in Malaysia needs to be thoroughly assessed. This review followed a PRISMA based systematic literature review. Literature search was performed in Scopus and Web of Science for articles between 2022 and 2024 with defined search string and inclusion criteria. After screening, 27 articles published in peer-review journals were identified for further screening. Thia review was synthesized in the following three themes: (i) Smart Farming and IoT Applications, (ii) Artificial Intelligence and Computer Vision, (iii) Sustainable Agriculture and Related Technologies. The review concludes that IoT-based smart farming enhances irrigation management, live monitoring, and resource utilization. Crop and weed detection are enabled by AI, computer vision technology to support early disease diagnosis and yield estimation using next generation of imaging and machine learning. Energy use and environmental pollution can be reduced by sustainable mechanization technologies. Despite these advantages, the barriers of high implementation cost, low digital literacy, and inconsistent policy enforcement hinder the widespread adoption of Malaysian smallholders. Adoption of IoT and AI technology with sustainable mechanization as the solution can serve as a promising approach in modernizing Malaysian agriculture. Advance mechanisms, cost-effective innovations and focused training programmes are necessary to enhanced productivity, resilience and environmental sustainability of the farming system.

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Published

2026-06-03

How to Cite

Baharudin, M. E., Saad, M. S., Zakaria, M. Z., Mohd Nor, A., & Mustafa, A. F. (2026). MECHANIZATION IN MALAYSIAN AGRICULTURE: A SYSTEMATIC REVIEW OF PRODUCTIVITY, SUSTAINABILITY, AND SOCIO-ECONOMIC PERSPECTIVES. Jurnal Mekanikal, 49(1), 164–178. https://doi.org/10.11113/jm.v49.713

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Section

Mechanical

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