Transformasi Digital Pertanian Melalui Smart Agriculture: Perspektif Riset Informatika
Kata Kunci:
Kata Kunci: Smart Agriculture, Internet of Things, Transformasi Digital, Kecerdasan Buatan, Sistem Informasi PertanianAbstrak
Transformasi digital di dalam sektor pertanian berkembang pesat melalui penerapan smart agriculture yang mengintegrasikan teknologi informatika seperti Internet of Things (IoT), big data, dan kecerdasan buatan untuk meningkatkan efisiensi dan produktivitas. Namun, adopsi teknologi ini masih harus menyesuaikan berbagai kendala, seoerti dalam aspek infrastruktur dan literasi digital. Penelitian ini bertujuan untuk mengetahui peran teknologi informatika dalam mendukung transformasi digital pertanian serta merancang kerangka sistem smart agriculture yang terintegrasi. Penelitian menggunakan metode tinjauan pustaka dengan menggunaka pendekatan kualitatif-deskriptif, dengan cara pengumpulan dan analisis dari sumber ilmiah yang relevan, kemudian dilakukan analisis konseptual untuk menyusun model sistem. Hasil penelitian menunjukkan bahwa smart agriculture terdiri dari lima lapisan utama, yaitu pengumpulan data, komunikasi, pemrosesan data, aplikasi, dan otomatisasi. Integrasi teknologi tersebut mampu menghasilkan informasi real-time seperti prediksi panen, rekomendasi irigasi, serta deteksi hama, yang meningkatkan akurasi pengambilan keputusan dan efisiensi penggunaan sumber daya. Selain itu, sistem memiliki mekanisme feedback loop yang memungkinkan peningkatan kinerja secara berkelanjutan. Penelitian ini menegaskan bahwa smart agriculture berpotensi besar dalam mendukung transformasi digital pertanian, meskipun implementasinya memerlukan dukungan infrastruktur dan peningkatan kapasitas pengguna. Penelitian selanjutnya disarankan untuk mengembangkan sistem yang lebih sederhana dan adaptif terhadap kondisi lokal.
Unduhan
Referensi
REFERENSI
[1] S. Alam, J. Kundu, S. Ghosh, and A. Dey, “Trusted Fuzzy Routing Scheme in Flying Ad-hoc Network,” J. Fuzzy Ext. Appl., vol. 5, no. 1, pp. 48–59, 2024, doi: 10.22105/jfea.2024.436052.1370.
[2] E. Effah, O. Thiare, and A. M. Wyglinski, “Hardware Evaluation of Cluster-Based Agricultural IoT Network,” IEEE Access, vol. 12, pp. 33628–33651, 2024, doi: 10.1109/ACCESS.2024.3370230.
[3] I. Ruiz-García et al., “Sustainable Occupancy Sensing Platform via Triboelectric and Piezoresistive Pressure Sensors,” IEEE Sensors Lett., vol. 9, no. 8, 2025, doi: 10.1109/LSENS.2025.3589020.
[4] N. Boufares, Y. Ben Saied, and L. Saïdane, “A Lightweight Three Dimensional Redeployment Algorithm for Distributed Mobile Wireless Sensor Networks,” Wirel. Pers. Commun., vol. 135, no. 2, pp. 835–873, 2024, doi: 10.1007/s11277-024-11078-3.
[5] D. Loukatos, A. Fragkos, G. Kargas, and K. G. Arvanitis, “Implementation and Evaluation of a Low-Cost Measurement Platform over LoRa and Applicability for Soil Monitoring,” Futur. Internet, vol. 16, no. 12, 2024, doi: 10.3390/fi16120443.
[6] M. Tabassum et al., “Enhance data availability and network consistency using artificial neural network for IoT,” Multimed. Tools Appl., vol. 83, no. 1, pp. 3111–3131, 2024, doi: 10.1007/s11042-022-13337-6.
[7] M. Al-Ambusaidi, Z. Zhang, Y. Muhammad, and A. Yahya, “ML-IDS: an efficient ML-enabled intrusion detection system for securing IoT networks and applications,” Soft Comput., vol. 28, no. 2, pp. 1765–1784, 2024, doi: 10.1007/s00500-023-09452-7.
[8] Z. Hu, Y. Qi, S. Jia, Y. Sun, Q. Li, and G. Shi, “A Soil Moisture Sensing System Powered by Self-Harvesting Soil Energy,” IEEE Sens. J., vol. 25, no. 9, pp. 15356–15366, 2025, doi: 10.1109/JSEN.2025.3551324.
[9] M. Ma, Z. Wang, S. Guo, and H. Lu, “Cloud–Edge Framework for AoI-Efficient Data Processing in Multi-UAV-Assisted Sensor Networks,” IEEE Internet Things J., vol. 11, no. 14, pp. 25251–25267, 2024, doi: 10.1109/JIOT.2024.3392244.
[10] P. Gangwani, A. Perez-Pons, and H. Upadhyay, “Evaluating Trust Management Frameworks for Wireless Sensor Networks,” Sensors, vol. 24, no. 9, 2024, doi: 10.3390/s24092852.
[11] S. Singh, A. S. Nandan, G. Sikka, A. Malik, and P. K. Singh, “RETRACTED ARTICLE: Genetic algorithm-based data controlling method using IoT-enabled WSN in power grid,” Soft Comput., vol. 27, no. 15, p. 11055, 2023, doi: 10.1007/s00500-022-07186-6.
[12] X. Zang, T. Wang, X. Zhang, J. Gong, P. Gao, and G. Zhang, “Encrypted malicious traffic detection based on natural language processing and deep learning,” Comput. Networks, vol. 250, 2024, doi: 10.1016/j.comnet.2024.110598.
[13] R. I. Mukhamediev et al., “Coverage Path Planning Optimization of Heterogeneous UAVs Group for Precision Agriculture,” IEEE Access, vol. 11, pp. 5789–5803, 2023, doi: 10.1109/ACCESS.2023.3235207.
[14] M. N. Mowla, N. Mowla, A. F. M. S. Shah, K. M. Rabie, and T. Shongwe, “Internet of Things and Wireless Sensor Networks for Smart Agriculture Applications: A Survey,” IEEE Access, vol. 11, pp. 145813–145852, 2023, doi: 10.1109/ACCESS.2023.3346299.
[15] A. K. Rao, K. K. Nagwanshi, and M. K. Shukla, “An optimized secure cluster-based routing protocol for IoT-based WSN structures in smart agriculture with blockchain-based integrity checking,” Peer-to-Peer Netw. Appl., vol. 17, no. 5, pp. 3159–3181, 2024, doi: 10.1007/s12083-024-01748-1.
[16] J. Liu, Z. Xu, and Z. Wen, “Joint Data Transmission and Trajectory Optimization in UAV-Enabled Wireless Powered Mobile Edge Learning Systems,” IEEE Trans. Veh. Technol., vol. 72, no. 9, pp. 11617–11630, 2023, doi: 10.1109/TVT.2023.3265479.
[17] Z. Lin, “Communication optimisation of smart agriculture wireless sensor network based on improved ant colony algorithm,” Int. J. Grid Util. Comput., vol. 15, no. 3–4, pp. 211–219, 2024, doi: 10.1504/IJGUC.2024.140106.
[18] S. Itoo, A. A. Khan, M. Ahmad, and M. J. Idrisi, “A Secure and Privacy-Preserving Lightweight Authentication and Key Exchange Algorithm for Smart Agriculture Monitoring System,” IEEE Access, vol. 11, pp. 56875–56890, 2023, doi: 10.1109/ACCESS.2023.3280542.
[19] B. Balamurugan et al., “Real time multi view image based FPC plant management with SS data security and low rate attack detection for efficient smart agriculture in WSN,” J. Intell. Fuzzy Syst., vol. 44, no. 1, pp. 91–100, 2023, doi: 10.3233/JIFS-220594.
[20] S. Rahmadika, W. Agustiarmi, R. Fikri, and B. J. Kweka, “Synergistic Disruption: Harnessing AI and Blockchain for Enhanced Privacy and Security in Federated Learning,” J. Online Inform., vol. 10, no. 1, pp. 22–31, 2025, doi: 10.15575/join.v10i1.1392.
[21] S. Craven et al., “Smart Bluetooth Stakes: Deployment of Soil Moisture Sensors with Rotating High-Gain Antenna Receiver on Center Pivot Irrigation Boom in a Commercial Wheat Field,” Sensors, vol. 25, no. 17, 2025, doi: 10.3390/s25175537.
[22] P. M. Maniraj Kumar, P. Nagarajan, A. Kaleel Rahuman, and T. Gobinath, “A Fuzzy Congestion Control in Wireless Sensor Networks based on Spider Monkey Optimization Algorithm,” IETE J. Res., vol. 70, no. 8, pp. 6893–6900, 2024, doi: 10.1080/03772063.2024.2310123.
[23] K. Bouarroudj, F. Babaa, and A. Touil, “IoT-based monitoring and control for optimized plant growth in smart greenhouses using soil and hydroponic systems,” Internet Things (The Netherlands), vol. 33, 2025, doi: 10.1016/j.iot.2025.101710.
[24] Z. Pan et al., “Wind-Wave Synergistic Triboelectric Nanogenerator: Performance Evaluation Test and Potential Applications in Offshore Areas,” Micromachines, vol. 15, no. 3, 2024, doi: 10.3390/mi15030314.
[25] G. Zhou, M. Peng, Y. Li, J. Wang, and C. Lian, “Secure transmission of wireless energy-carrying communication systems for the Internet of Things,” Appl. Math. Nonlinear Sci., vol. 8, no. 1, pp. 3135–3148, 2023, doi: 10.2478/amns.2023.1.00026.
[26] V. Choudhary and S. Tanwar, “Generation & evaluation of datasets for anomaly-based intrusion detection systems in IoT environments,” Multimed. Tools Appl., vol. 83, no. 36, pp. 84331–84355, 2024, doi: 10.1007/s11042-024-19066-2.
[27] B. Kumara and S. A. Padmanabhan, “A condition-based distributed approach for secured privacy preservation of nodes in wireless sensor networks IoT,” Int. J. Reconfigurable Embed. Syst., vol. 13, no. 2, pp. 441–449, 2024, doi: 10.11591/ijres.v13.i2.pp441-449.
[28] S. Li, Y. Ji, W. Peng, H. Dai, and J. Jiang, “A social relationship-aware collaborative D2D secure caching strategy,” IET Commun., vol. 19, no. 1, 2025, doi: 10.1049/cmu2.70009.
[29] Y. W. Kim, S. H. Choi, and T. H. Han, “Rapid Topology Generation and Core Mapping of Optical Network-on-Chip for Heterogeneous Computing Platform,” IEEE Access, vol. 9, pp. 110359–110370, 2021, doi: 10.1109/ACCESS.2021.3102270.
[30] K. C. Kalpavi and S. B. Sujatha, “Dual step hybrid routing protocol for network lifetime enhancement in WSN-IoT environment,” Int. J. Reconfigurable Embed. Syst., vol. 13, no. 2, pp. 323–331, 2024, doi: 10.11591/ijres.v13.i2.pp323-331.
[31] F. P. E. Putra, M. A. Mahmud, and I. S. Maqom, “Pengembangan Sistem Pemantauan Lingkungan Berbasis Internet of Things (IoT) di Kampus,” 2023, researchgate.net. [Online]. Available: https://www.researchgate.net/profile/Fauzan-Eka-Putra-2/publication/379445633_Pengembangan_Sistem_Pemantauan_Lingkungan_Berbasis_Internet_of_Things_IoT_di_Kampus/links/6609aa9010ca86798731de49/Pengembangan-Sistem-Pemantauan-Lingkungan-Berbasis-Internet-of
[32] F. P. E. Putra, A. Muzayyin, and M. U. Mansyur, “ANALISIS KUALITAS LAYANAN ABSENSI BERBASIS FINGER BERDASARKAN Quality of Service,” J. Inform., 2024, doi: https://doi.org/10.30873/ji.v24i1.3949.
[33] F. Prasetyo, E. Putra, F. Muslim, and R. Paradina, “Technical Performance Comparison of Modern Frontend Frameworks Study on Svelte , React , and Vue,” vol. 5, no. 1, pp. 355–364, 2025.
[34] J. Informatika, F. Prasetyo, E. Putra, A. Vidyan, and M. Ali, “Evaluasi Kualitas Layanan ( QoS ) pada Jaringan Wi-Fi 6 Dibandingkan dengan Wi-Fi 5”.
[35] F. Prasetyo, E. Putra, A. Zulfikri, A. Rohman, and R. Alim, “Analysis Comparative of Performance Optimization Techniques for PHP Framework Testing : Laravel , CodeIgniter , Symfony,” vol. 5, no. 1, pp. 242–248, 2025.
[36] F. Prasetyo, E. Putra, M. Mursidi, and D. Wahid, “Sistem Pengendali Lingkungan Pertanian Dengan Wireless Sensor Network Untuk Mengoptimalkan Budidaya Hidroponik,” vol. 3, no. 2, pp. 931–937, 2024.
[37] J. Informatika, F. P. E. Putra, L. Romadona, and S. F. Rohmah, “Implementasi dan Evaluasi Protokol QUIC untuk Optimalisasi Kinerja Streaming Video Real-Time pada Jaringan 5G,” pp. 0–7.
[38] F. Prasetyo, E. Putra, M. Dafid, and I. Syafi, “Firewall Implementation as a Computer Network Security Strategy for Data Protection,” vol. 5, no. 1, pp. 291–297, 2025.
[39] F. Prasetyo, E. Putra, M. Nazir, and Y. Zain, “OPTIMASI PENILAIAN PADA E - LEARNING UNIVERSITAS MADURA DENGAN MENGGUNAKAN,” vol. 20, no. 2, pp. 118–126, 2020.
[40] F. Prasetyo, E. Putra, N. Ramadhani, and M. Mursidi, “Service Quality Analysis of RFID - Based Smart Door Lock in Front One Azana Style Hotel Area,” vol. 4, no. 1, pp. 372–381, 2024.
[41] N. Duy Tan, D.-N. Nguyen, H.-N. Hoang, and T.-T.-H. Le, “EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT Applications,” Computers, vol. 12, no. 5, 2023, doi: 10.3390/computers12050103.
[42] J. Xu et al., “Chemically Driven Sintering of Colloidal Cu Nanocrystals for Multiscale Electronic and Optical Devices,” ACS Nano, vol. 18, no. 27, pp. 17611–17621, 2024, doi: 10.1021/acsnano.4c02007.
[43] N. Suresh Kumar and G. Santhosh Kumar, “Abstracting IoT protocols using timed process algebra and SPIN model checker,” Cluster Comput., vol. 26, no. 2, pp. 1611–1629, 2023, doi: 10.1007/s10586-022-03963-y.
[44] S. Khan, T. Mazhar, T. Shahzad, Y. Y. Yasin, and H. Hamam, “Integrating IoT and WSN: Enhancing quality of service through energy efficiency, scalability, and secure communication in smart systems,” Peer-to-Peer Netw. Appl., vol. 18, no. 5, 2025, doi: 10.1007/s12083-025-02070-0.
[45] R. Mishra et al., “nodeWSNsec: A Hybrid Metaheuristic Approach for Reliable Security and Node Deployment in Wireless Sensor Networks,” Int. J. Adv. Comput. Sci. Appl., vol. 16, no. 8, pp. 132–142, 2025, doi: 10.14569/IJACSA.2025.0160814.
[46] E. Geo Francis and S. Sheeja, “Enhanced intrusion detection in wireless sensor networks using deep reinforcement learning with improved feature extraction and selection,” Multimed. Tools Appl., vol. 84, no. 13, pp. 11943–11982, 2025, doi: 10.1007/s11042-024-19305-6.
[47] K. R. Raghava Rao, B. N. K. Reddy, and A. S. Sai Kumar, “Using advanced distributed energy efficient clustering increasing the network lifetime in wireless sensor networks,” Soft Comput., vol. 27, no. 20, pp. 15269–15280, 2023, doi: 10.1007/s00500-023-07940-4.
[48] Z. Wang, N. Dong, J. Sun, W. Knottenbelt, and Y. Guo, “ZkFL :Zero-Knowledge Proof-Based Gradient Aggregation for Federated Learning,” IEEE Trans. Big Data, vol. 11, no. 2, pp. 447–460, 2025, doi: 10.1109/TBDATA.2024.3403370.
[49] Y. Cheng, Y. Hu, W. Liu, and M. Bilal, “Federated learning with adaptive local aggregation for privacy-aware recommender systems in Internet of Vehicles,” Inf. Sci. (Ny)., vol. 710, 2025, doi: 10.1016/j.ins.2025.122100.
[50] J. Stocchero, A. Dexheimer Carneiro, I. Zacarias, and E. Pignaton De Freitas, “Combining information centric and software defined networking to support command and control agility in military mobile networks,” Peer-to-Peer Netw. Appl., vol. 16, no. 2, pp. 765–784, 2023, doi: 10.1007/s12083-022-01443-z.
[51] F. Prasetyo, E. Putra, I. N. S. Degeng, S. Ulfa, and W. Kamdi, “The Evolution of Quality Education : Impacts and Challenges of Using Open Educational Resources ( OER ) and Open Educational Practices ( OEP ) in the Conceive - Design - Implement - Operate ( CDIO ) Framework,” vol. 13, no. 1, pp. 386–395, 2024, doi: 10.18421/TEM131.
Unduhan
Diterbitkan
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2026 Ahmad Hamdani, Moh. Izzul Haq Ramadlani (Penulis)

Artikel ini berlisensi Creative Commons Attribution 4.0 International License.








