Analisis Simulasi Optimasi Konsumsi Energi pada Sistem Smart Agriculture Berbasis IoT untuk Monitoring dan Irigasi Otomatis
Kata Kunci:
Smart Agriculture, Internet of Things, Optimasi Energi, Irigasi Otomatis, Simulasi Konsumsi EnergiAbstrak
Penerapan smart agriculture berbasis Internet of Things memungkinkan monitoring kondisi lingkungan dan pengendalian irigasi dilakukan secara otomatis. Namun, aktivitas pembacaan sensor, komunikasi data, dan pengoperasian pompa dapat meningkatkan konsumsi energi, sehingga diperlukan strategi optimasi agar sistem tetap efisien tanpa mengurangi fungsi utama irigasi. Penelitian ini bertujuan menganalisis potensi penghematan energi pada sistem smart agriculture berbasis IoT melalui pengaturan interval pembacaan sensor, pengiriman data, dan aktivitas pompa, serta mengevaluasi pengaruhnya terhadap kelembapan tanah. Penelitian menggunakan pendekatan kuantitatif berbasis simulasi dengan dua skenario, yaitu tanpa optimasi dan dengan optimasi. Skenario tanpa optimasi menggunakan interval pembacaan sensor dan pengiriman data setiap 5 detik, sedangkan skenario optimasi menggunakan interval pembacaan sensor 30 detik dan pengiriman data 60 detik. Parameter yang dianalisis meliputi tegangan, arus, daya, energi total, frekuensi aktivasi pompa, durasi operasi pompa, dan kelembapan tanah. Hasil simulasi menunjukkan konsumsi energi sebesar 3,16 Wh pada skenario tanpa optimasi dan 2,34 Wh pada skenario optimasi, sehingga diperoleh potensi penghematan energi sebesar 25,95%. Arus rata-rata menurun dari 315 mA menjadi 234 mA, sedangkan daya rata-rata menurun dari 1,58 W menjadi 1,17 W. Kelembapan tanah akhir tercatat sebesar 70% pada skenario tanpa optimasi dan 68% pada skenario optimasi. Hasil tersebut menunjukkan bahwa strategi optimasi berpotensi menurunkan konsumsi energi tanpa menghasilkan perubahan besar pada kelembapan tanah akhir. Namun, hasil penelitian masih bersifat simulatif sehingga diperlukan implementasi prototipe dan pengujian eksperimental untuk memvalidasi kinerja sistem pada kondisi nyata.
Unduhan
Referensi
[1] A. Pourghasem, R. Kirner, A. Tsokanos, I. Mporas, and A. Mylonas, “Machine Learning and Deep Learning-Based Multi-Attribute Physical-Layer Authentication for Spoofing Detection in LoRaWAN,” Futur. Internet, vol. 17, no. 2, 2025, doi: 10.3390/fi17020068.
[2] C. Trigona, G. A. Salerno, N. Salerno, S. Baglio, and A. R. Bulsara, “Analytical modeling of tribo/piezoelectric transducers for energy harvesting from slow plant movements,” Meas. J. Int. Meas. Confed., vol. 256, 2025, doi: 10.1016/j.measurement.2025.118109.
[3] G. Asaamoning, P. Mendes, and N. Magaia, “A Dynamic Clustering Mechanism with Load-Balancing for Flying Ad Hoc Networks,” IEEE Access, vol. 9, pp. 158574–158586, 2021, doi: 10.1109/ACCESS.2021.3130417.
[4] 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.
[5] M. A. Akram, A. N. Mian, A. K. Biswas, S. Kumari, and C.-M. Chen, “Privacy-Preserving Lightweight LoRaWAN Authentication Protocol for IoT Applications,” IEEE Internet Things J., vol. 12, no. 20, pp. 42790–42802, 2025, doi: 10.1109/JIOT.2025.3593886.
[6] X. Xia et al., “Dynamic-environment-adaptive triboelectric nanogenerator utilizing wind-water energy synergy,” Chem. Eng. J., vol. 520, 2025, doi: 10.1016/j.cej.2025.165688.
[7] F. Prasetyo, E. Putra, R. N. Saputra, F. M. Haris, and S. Nur, “Application of Internet of Things Technology in Monitoring Water Quality in Fishponds,” Brill. Res. Artif. Intell., vol. 4, no. 1, pp. 356–361, 2024, doi: 10.47709/brilliance.v4i1.4231.
[8] F. P. E. Putra, S. R. Sutarsih, P. Permana, and M. U. Mansyur, “Optimalisasi Perancangan Aplikasi Manajemen Data Koloman, Di Desa Pulau Mandangin Sampang – Madura Berbasis Website,” RABIT J. Teknol. dan Sist. Inf. Univrab, vol. 9, no. 2, pp. 285–294, 2024, doi: 10.36341/rabit.v9i2.4840.
[9] A. Saha and M. A. Alam, “Practical and Thermodynamic Limits of Dual-Use, Potentiometric Energy Harvesters for Self-Powered Sensors,” ACS Appl. Energy Mater., vol. 8, no. 1, pp. 238–244, 2025, doi: 10.1021/acsaem.4c02320.
[10] R. Mishra, D. Ramesh, P. Bellavista, and D. R. Edla, “Redactable Blockchain-Assisted Secure Data Aggregation Scheme for Fog-Enabled Internet-of-Farming-Things,” IEEE Trans. Netw. Serv. Manag., vol. 20, no. 4, pp. 4652–4667, 2023, doi: 10.1109/TNSM.2023.3322442.
[11] 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.
[12] T. Mahjoub, A. Ben Mnaouer, M. B. Ben Said, and H. Boujemâa, “LoRa signal propagation and path loss prediction in Tunisian date palm oases,” Comput. Electron. Agric., vol. 222, 2024, doi: 10.1016/j.compag.2024.109027.
[13] J. Long and Z. Zhang, “Multiscale Wheat Lodging Parameter Detection Based on MobilenetV3,” 2024, Springer Nature Singapore. doi: 10.1007/978-981-97-6441-9_7.
[14] S. Ahmad, N. Akhtar, A. Ahmed, S. Iftikhar, S. Bawazeer, and S. Abdullah, “An Ensemble Formal Approach to Improve Energy Efficiency and Data Aggregation in Smart Agriculture,” IEEE Access, vol. 13, pp. 65316–65333, 2025, doi: 10.1109/ACCESS.2025.3558551.
[15] M. N. Fauzan, R. Munadi, S. Sumaryo, and H. H. Nuha, “Enhanced Grey Wolf Optimization for Efficient Transmission Power Optimization in Wireless Sensor Network,” Appl. Syst. Innov., vol. 8, no. 2, 2025, doi: 10.3390/asi8020036.
[16] V. Kumar, K. V Sharma, N. Kedam, A. Patel, T. R. Kate, and U. Rathnayake, “A comprehensive review on smart and sustainable agriculture using IoT technologies,” Smart Agric. Technol., vol. 8, 2024, doi: 10.1016/j.atech.2024.100487.
[17] S. K. Susee, M. S. Kumar, and B. Chidambararajan, “A novel homomorphic encryption-based optimization framework for wireless sensor networks,” Microsyst. Technol., vol. 31, no. 10, pp. 2961–2981, 2025, doi: 10.1007/s00542-025-05921-1.
[18] M. A. Tawfeek, N. Yanes, L. Menzli, G. Aldehim, and M. A. Mahmood, “Adaptive Deep Learning Model to Enhance Smart Greenhouse Agriculture,” Comput. Mater. Contin., vol. 77, no. 2, pp. 2545–2564, 2023, doi: 10.32604/cmc.2023.042179.
[19] K. V Reddy et al., “Edge AI in Sustainable Farming: Deep Learning-Driven IoT Framework to Safeguard Crops From Wildlife Threats,” IEEE Access, vol. 12, pp. 77707–77723, 2024, doi: 10.1109/ACCESS.2024.3406585.
[20] A. R. de A. Zanella, E. Da Silva, and L. C. P. Albini, “Security challenges to smart agriculture: Current state, key issues, and future directions,” 2020, Elsevier. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2590005620300333
[21] S. Lu and X. Xiao, “Neuromorphic Computing for Smart Agriculture,” 2024, MDPI AG. doi: 10.3390/agriculture14111977.
[22] F. Fauzan Prasetyo Eka Putra1, Syirofi, Moh.Mursidi, D. Wahid, and A. Nuraini, “Sistem Pengendali Lingkungan Pertanian Dengan Wireless Sensor Network Untuk Mengoptimalkan Budidaya Hidroponik,” Digit. Transform. Technol., vol. 3, no. 2, pp. 931–937, 2024, doi: 10.47709/digitech.v3i2.3461.
[23] P. Priya and G. Kaur, “Smart Sensors for Smart Agriculture,” 2021, IGI Global. doi: 10.4018/978-1-7998-1722-2.ch011.
[24] “IOT Based Smart Agriculture in Bangladesh: An Overview,” 2023, Eman Research Publishing LLC. doi: 10.25163/agriculture.119563.
[25] F. P. E. Putra, A. Baidawi, and A. A. Mubarok, “Merancang Jaringan Sensor Nirkabel dan IoT untuk Kota Pintar Pamekasan,” J. Inf. dan Teknol., vol. 5, no. 2, pp. 138–145, 2023, doi: 10.37034/jidt.v5i1.331.
[26] R. Yusuf and B. Sutejo, “MODEL KUANTITATIF OPTIMASI ENERGI ALTERNATIF BAHAN BAKAR MINYAK,” 2022, Universitas Muhammadiyah Gresik. doi: 10.30587/matrik.v22i2.3129.
[27] J. Informasi, F. Prasetyo, E. Putra, M. Riski, Y. R. Febriani, and M. U. Mansyur, “Optimization of Web Based Academic Information System Design to Increase Efficiency in Junior High Schools,” vol. 6, pp. 150–158, 2024, doi: 10.60083/jidt.v6i2.545.
[28] C. A. Rizki, N. Khairuniza, and M. Habibah, “Implementasi Sistem Pemantauan Daya Listrik Real-Time Berbasis ESP32 untuk Optimasi Energi,” 2025, CV. Raskha Media Group. doi: 10.64803/joeer.v1i2.11.
[29] K. Saminathan, L. Perumal, F. H. Shajin, and R. K. Shakya, “Multicast On-Route cluster propagation to detect network intrusion detection systems on MANET using Deep Operator Neural networks,” Expert Syst. Appl., vol. 271, 2025, doi: 10.1016/j.eswa.2024.125864.
[30] Z. Juroszek and M. Kudelko, “A model of optimization for local energy infrastructure development,” 2016, Elsevier BV. doi: 10.1016/j.energy.2015.12.083.
[31] J. Informatika et al., “Analisis Kinerja Jaringan 5G dalam Meningkatkan Konektivi- tas Internet of Things ( IoT ),” 2025.
[32] “99/02096 Optimization model for energy generation from agricultural residue,” 1999, Elsevier BV. doi: 10.1016/s0140-6701(99)97866-9.
[33] X. W, “Analytical Optimization of Hydraulic Fracturing,” 2024, Medwin Publishers. doi: 10.23880/jeesc-16000105.
[34] D. Finon, “About the Use of an Energy Optimization Model,” 1981, Springer Netherlands. doi: 10.1007/978-94-009-8585-8_8.
[35] J. Sistim, F. Prasetyo, E. Putra, S. M. Dewi, and A. Hamzah, “Privasi dan Keamanan Penerapan IoT Dalam Kehidupan Sehari-Hari : Tantangan dan Implikasi,” vol. 5, no. 2, pp. 26–32, 2023, doi: 10.37034/jsisfotek.v5i1.232.
[36] Y. Cao, H. N. Rad, D. H. Jamali, N. Hashemian, and A. Ghasemi, “A novel multi-objective spiral optimization algorithm for an innovative solar/biomass-based multi-generation energy system: 3E analyses, and optimization algorithms comparison,” 2020, Elsevier BV. doi: 10.1016/j.enconman.2020.112961.
[37] P. Baredar, V. Khare, and S. Nema, “Biogas energy system,” 2020, Elsevier. doi: 10.1016/b978-0-12-822718-3.00001-0.
[38] “Ecologically-inspired optimization modelling of urban energy systems,” 2013, Routledge. doi: 10.4324/9780203066782-22.
[39] R. K. Jain, A. Mukherjee, P. Karmakar, A. Banerjee, H. Akbarov, and S. Hasanov, “Experimental performance of soil monitoring system using IoT technique for automatic drip irrigation,” Int. J. Commun. Syst., vol. 36, no. 18, 2023, doi: 10.1002/dac.5617.
[40] N. Majumder et al., “Automatic Plant Irrigation System ,” 2023, Society for Makers, Artists, Researchers and Technologists. doi: 10.15864/ijiip.4403.
[41] K. Shahverdi, “AICSS: Automatic simulator–controller/optimizer model of open channels,” 2023, Wiley. doi: 10.1002/ird.2852.
[42] I. Ali, S. Warisma, and A. Aljabar, “Arduino Microcontroller-Based Automatic Irrigation System for Grape Cultivation,” 2025, Yayasan Kita Menulis. doi: 10.59934/jaiea.v5i1.1477.
[43] F. P. E. Putra, N. Ramadhani, F. Fauzan, and ..., “Service Quality Analysis of RFID-Based Smart Door Lock in Front One Azana Style Hotel Area,” … Res. Artif. …, 2024, doi: 10.47709/brilliance.v4i1.4292.
[44] H. Kwon, S. Grunwald, H. Beck, and Y. Jung, “AUTOMATIC CALIBRATION OF A HYDROLOGIC MODEL FOR SIMULATING GROUNDWATER TABLE FLUCTUATIONS ON FARMS IN THE EVERGLADES AGRICULTURAL AREA OF SOUTH FLORIDA,” 2014, Wiley. doi: 10.1002/ird.1822.
[45] Y. Simamora, S. Sukmajati, and R. Afrianda, “OPTIMASI REKONFIGURASI JARINGAN DISTRIBUSI RADIAL UNTUK MEMINIMALKAN RUGI JARINGAN MENGGUNAKAN METODE SIMPLE BRANCH EXCHANGE,” 2019, Sekolah Tinggi Teknik-PLN. doi: 10.33322/energi.v10i2.218.
[46] F. Prasetyo, E. Putra, O. F. Kusuma, M. Mursidi, and A. Hamzah, “Comparative Analysis of Laravel and Symfony in PHP-Based Web Application Developmen,” vol. 5, no. 1, pp. 272–280, 2025, doi: 10.47709/brilliance.v5i1.5892.
[47] I. H. Osei and E. O. Osei, “Multipath Energy Optimization Broadcast Routing Protocol for Wireless Sensor Network Using Genetic Algorithm and Ant Colony Optimization,” 2023, Elsevier BV. doi: 10.2139/ssrn.4358067.
[48] M. A. Mohammed, A. D. Farhood, and A. J. Abid, “A smart energy consumption manager based on protues simulation,” 2020, Institute of Advanced Engineering and Science. doi: 10.11591/ijpeds.v11.i1.pp143-150.
[49] S. Zhan and A. Chong, “A Robust Unsupervised Framework for High-resolution Building Energy Consumption Profiling,” 2020, IBPSA. doi: 10.26868/25222708.2019.210994.
[50] D. Andritsou, C. Alexiou, and C. Potsiou, “BIM, 3D Cadastral Data and AI for Weather Conditions Simulation and Energy Consumption Monitoring,” 2024, MDPI AG. doi: 10.3390/land13060880.
Diterbitkan
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2026 Dimas Prasetya Januardiansyah, Achmed Abdillah (Penulis)
Artikel ini berlisensi Creative Commons Attribution 4.0 International License.
