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Analysing the Potential of Agricultural Technology Integration in Crop Monitoring Systems to Improve the Efficiency of Soybean Cultivation Marina, Ida; Bastian, Ade; Indriana, Kovertina Rakhmi; Sukmawati, Dety; Komariah, Ai; Hasnah, Imas Naimah; Mukhlis
Jurnal Penelitian Pendidikan IPA Vol 11 No 12 (2025): December
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i12.13361

Abstract

This study aims to integrate modern agricultural technology into soybean cultivation through the application of an Internet of Things (IoT)-based crop monitoring system combined with artificial intelligence (AI) and cloud-based data processing. The research was conducted at two experimental sites to evaluate system performance under different environmental conditions. IoT sensors and AI algorithms were utilized to monitor soil moisture, temperature, and plant health, optimize irrigation, detect pests, predict yield, and analyze plant health. Data collected included irrigation efficiency, pest control effectiveness, and plant health, which were analyzed using statistical methods. The results showed that the implementation of IoT-based monitoring technology significantly improved the technical efficiency of soybean farming by optimizing the use of land, fertilizer, and labor. Farms using monitoring technology achieved an average technical efficiency score of 0.991, higher than farms without technology, which only reached 0.920. In addition, the technology reduced water and fertilizer wastage, increased productivity, and supported data-driven agricultural decision-making. In conclusion, the application of IoT- and AI-based crop monitoring systems enhances the sustainability and productivity of soybean farming and provides an effective approach to improving agricultural efficiency in modern farming systems.