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All Journal Agrivet : Jurnal Ilmu-Ilmu Pertanian dan Peternakan (Journal of Agricultural Sciences and Veteriner) Jurnal Penelitian Pendidikan IPA (JPPIPA) Paspalum: Jurnal Ilmiah Pertanian BERNAS: Jurnal Pengabdian Kepada Masyarakat Pro-Stek Journal of Innovation and Research in Agriculture Journal of Sustainable Agribusiness
Ida Marina
Program Study Agribisnis Fakultas Pertanian Universitas Majalengka
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Analysing the Potential of Agricultural Technology Integration in Crop Monitoring Systems to Improve the Efficiency of Soybean Cultivation Ida Marina; Ade Bastian; Kovertina Rakhmi Indriana; Dety Sukmawati; Ai Komariah; Imas Naimah Hasnah; 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.
Co-Authors Ade Bastian Adi Oksifa Rahma adi oksifa rahma harti Adi Oksifa Rahma Harti Agyn Akhmad Gimnastiar Ai Komariah Dadan Ramdani Nugraha Dede Cahyana Dede Erni Nurasia Dede Salim Nahdi Dena Ismaya Dety Sukmawati Dinar Dinar Dinar Dinar DINAR, DINAR Edang Juliana Eka Risnawati Euis Dasipah Faliq Aghna Harkhan Ghisha Aulia Andriani Hikmah Riana Sah Roni Imas Naimah Hasnah Istiqomatur Ramdhaniah Izzal Taufik Nursalam Jajang Nurjaman Jaka Sulaksana Kosasih Somantri Kosasih Sumantri Kovertina Rakhmi Indriana Leli Nurul Hidayah Liffi Halimatul Izzah Mahpud Iwan Merry Elviyenny Muhammad Fahrudin Mukhlis Nina Apriyani Nur Suciati Ramadan Rizky Agustina Ningrum Rizky Munfariz Saeful Mahmud Sinta Noviyan Siti Aisyah Sri Ayu Andayani Sri Umyati Sukmasari, Miftah Dieni Tika Efrida Yunita Umar Dani Zahra Nur Safa