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All Journal Journal of Computer Science Application and Engineering Jurnal Sistem Informasi dan Teknik Informatika (JAFOTIK)
Anwar, Ican
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Other

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Journal : Journal of Computer Science Application and Engineering

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Shaping the Future of Agriculture with Intelligent Systems Anwar, Ican
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 3 No. 2 (2025): JOSAPEN - July
Publisher : PT. Lentera Ilmu Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70356/josapen.v3i2.72

Abstract

This study explores the implementation of intelligent systems in agriculture as a solution to longstanding challenges such as inefficient resource use, disease management, and low productivity. By integrating technologies like Artificial Intelligence (AI), the Internet of Things (IoT), computer vision, and robotics, intelligent systems enable precision farming that optimizes water usage, enhances crop monitoring, automates labor-intensive tasks, and improves overall decision-making. Real-world applications such as CropX and NetBeat for smart irrigation, Plantix and Nuru for disease detection, and John Deere’s autonomous tractors for automated fieldwork demonstrate the tangible benefits of these innovations. Additionally, tools like Moocall and Ida offer real-time livestock health monitoring, while platforms such as AgriPredict and aWhere provide data-driven decision support to farmers globally. A sample block diagram of a smart irrigation system, supported by a simplified calculation, illustrates the practical operation and measurable benefits of such systems. The study emphasizes the potential of intelligent agriculture not only to boost productivity and sustainability but also to make advanced tools more accessible to small and medium-scale farmers. Future advancements should aim to enhance integration, affordability, and ease of use, ultimately supporting the transition to more resilient and efficient agricultural practices in the face of growing global food demands.
From Traditional to Intelligent Agriculture: A Vision for the Future Anwar, Ican
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 4 No. 1 (2026): JOSAPEN - January
Publisher : PT. Lentera Ilmu Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70356/josapen.v4i1.94

Abstract

The transition from traditional agriculture to intelligent, data-driven farming systems is increasingly critical for addressing challenges related to climate change, resource limitations, and food security. This study presents a comprehensive framework for intelligent agriculture by integrating Internet of Things technologies, machine learning techniques, and decision support systems to enhance agricultural productivity and sustainability. The proposed approach follows a structured methodology involving data acquisition, preprocessing, feature selection, intelligent modeling, and performance evaluation. Experimental results indicate that intelligent agriculture improves water-use efficiency by approximately 28%, reduces fertilizer usage by 22%, and enhances crop yield prediction accuracy from 62% to 88% when compared with traditional farming practices. Early pest and disease detection capabilities are improved by nearly 35%, enabling timely intervention and reduced crop losses. These findings demonstrate that intelligent agriculture significantly outperforms conventional methods while promoting sustainable resource management. Despite challenges related to infrastructure and adoption, the study confirms that intelligent agriculture represents a promising and resilient solution for future agricultural systems.
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