SIMULASI SISTEM MONITORING LENGAS TANAH BERBASIS ADC DAN KENDALI IRIGASI OTOMATIS MENGGUNAKAN METODE HYSTERESIS UNTUK APLIKASI PERTANIAN PRESISI

Ardan Wiratmoko; Andri Prima Nugroho; Murtiningrum; Gigieh Henggar Jaya; Saifuddin Afif; Mukhes Sri Muna; Agapetalia Indriyawati; Lilik Sutiarso

doi:10.35760/jpp.2026.v10i1.259

Penulis

Ardan Wiratmoko Universitas Gadjah Mada Penulis
Andri Prima Nugroho Universitas Gadjah Mada Penulis
Murtiningrum Universitas Gadjah Mada Penulis
Gigieh Henggar Jaya Universitas Gadjah Mada Penulis
Saifuddin Afif Universitas Gadjah Mada Penulis
Mukhes Sri Muna Universitas Gadjah Mada Penulis
Agapetalia Indriyawati Universitas Gadjah Mada Penulis
Lilik Sutiarso Universitas Gadjah Mada Penulis

DOI:

https://doi.org/10.35760/jpp.2026.v10i1.259

Kata Kunci:

ADC, hysteresis, irigasi otomatis, lengas tanah, pertanian presisi

Abstrak

Penelitian ini bertujuan mensimulasikan sistem monitoring lengas tanah berbasis Analog to Digital Converter (ADC) dan kendali irigasi otomatis menggunakan metode hysteresis untuk aplikasi pertanian presisi. Model simulasi dikembangkan secara komputasional menggunakan Python dengan merepresentasikan alur akuisisi sinyal sensor, penambahan noise, pengondisian sinyal menggunakan filter RC low-pass, konversi analog-ke-digital, estimasi Volumetric Water Content (VWC), serta keputusan aktuasi pompa. Sensor lengas tanah dimodelkan menghasilkan tegangan 0,50–2,50 V yang merepresentasikan 0–60% VWC. Hasil simulasi menunjukkan bahwa ADC 12 bit dengan tegangan referensi 3,30 V menghasilkan resolusi 0,8059 mV/count dan estimasi resolusi lengas tanah sebesar 0,0242% VWC/count. Frekuensi sampling 20,00 Hz memenuhi kriteria Nyquist, sedangkan filter RC mampu menurunkan RMSE dari 197,06 mV menjadi 68,18 mV. Kendali hysteresis dengan ambang ON pada VWC<25% dan OFF pada VWC>38% menghasilkan respons pompa yang stabil dengan duty cycle 15,28% selama simulasi 72 jam. Simulasi ini menunjukkan bahwa integrasi ADC, pengondisian sinyal, dan hysteresis berpotensi menjadi dasar pengembangan sistem irigasi presisi berbasis monitoring lengas tanah.

Unduhan

Data unduhan tidak tersedia.

Biografi Penulis

Ardan Wiratmoko, Universitas Gadjah Mada

Smart Agriculture Research Center, Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada
Andri Prima Nugroho, Universitas Gadjah Mada

Smart Agriculture Research Center, Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada.
Murtiningrum, Universitas Gadjah Mada

Smart Agriculture Research Center, Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada
Gigieh Henggar Jaya, Universitas Gadjah Mada

Department of Agricultural Engineering, Faculty of Agriculture, Universitas Jenderal Soedirman.
Saifuddin Afif, Universitas Gadjah Mada

Smart Agriculture Research Center, Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada.
Mukhes Sri Muna, Universitas Gadjah Mada

Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Udayana
Agapetalia Indriyawati, Universitas Gadjah Mada

Biosystems Engineering Study Program, Faculty of Industrial Technology, Institut Teknologi Sumatera.
Lilik Sutiarso, Universitas Gadjah Mada

Smart Agriculture Research Center, Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada

Referensi

Abioye, E.A., Abidin, M.S.Z., Mahmud, M.S.A., Buyamin, S., AbdRahman, M.K.I., Otuoze, A.O., Ramli, M.S.A., Ijike, O.D. 2021. IoT-based monitoring and data-driven modelling of drip irrigation system for mustard leaf cultivation experiment. Information Processing in Agriculture 8, 270–283.

Afif, S., Wiratmoko, A., Nugroho, A.P., Okayasu, T., Sutiarso, L. 2025. Design of Smart Plant Electrical Signal Monitoring System for Indoor Farming. BIO Web Conf. 167, 05004.

Kandamali, D.F., Kiobia, D.O., Ngimbwa, P.C., Mwitta, C.J., McLemore, A., Porter, E., Porter, W., Rains, G.C. 2025. Soil Moisture Prediction Using LSTM And Ensemble Learning Methods. IFAC-PapersOnLine 59, 297–302.

Kumar, V., Sharma, K.V., Kedam, N., Patel, A., Kate, T.R., Rathnayake, U. 2024. A comprehensive review on smart and sustainable agriculture using IoT technologies. Smart Agricultural Technology 8, 100487.

Maniam, S., Tee, Y.-K., Memar, E., Wong, H.Y., Zaman, M. 2026. Smart irrigation management: IoT-based RNN-LSTM model for soil moisture prediction in precision agriculture. Smart Agricultural Technology 13, 101866.

Nugroho, A.P., Kusumawati, N.B., Murtiningrum, Wiratmoko, A., Haryadi, I.M., Pradana, F.A., Suwardi, Sukarman, Primananda, S., Sutiarso, L. 2023. Development of Soil Moisture Content Monitoring System for Precision Measurement of Soil Moisture in Sub-Optimal Land for Palm Oil Plantation. BIO Web Conf. 69, 05003.

Nugroho, A.P., Wiratmoko, A., Nugraha, D., Markumningsih, S., Sutiarso, L., Falah, M.A.F., Okayasu, T., 2025. Development of a low-cost thermal imaging system for water stress monitoring in indoor farming. Smart Agricultural Technology 11, 101048.

Nugroho, A.P., Wiratmoko, A., Oktasari, U.D., Kusumawardani, R.F., Pradana, F.A., Sutiarso, L., Sukarman, Suwardi, Primananda, S., Okayasu, T. 2026. A confidence-weighted decision framework for on-site fertilizer quality screening and off-spec detection in smart agricultural systems using low-cost macronutrient sensors. Smart Agricultural Technology 102103.

Payero, J.O., Sekaran, U., Turner, D.B. 2026. Using a wireless sensor network and the Internet of Things (IoT) to automate a lateral move irrigation system based on real-time soil water potential data. Smart Agricultural Technology 14, 102003.

Pramanik, M., Khanna, M., Singh, M., Singh, D.K., Sudhishri, S., Bhatia, A., Ranjan, R. 2022. Automation of soil moisture sensor-based basin irrigation system. Smart Agricultural Technology 2, 100032.

Progga, J.F., Zhang, X., Maiti, S., Sun, X., Dey, S., Eshkabilov, S., Feng, X. 2026. A chip-based radio frequency sensor for soil moisture measurements: A machine learning and deep learning calibration approach. J. Agric. Food Res. 25, 102591.

Ramli, R.M., Jabbar, W.A. 2022. Design and implementation of solar-powered with IoT-Enabled portable irrigation system. Internet of Things and Cyber-Physical Systems 2, 212–225.

Rudrakar, S., Rughani, P. 2024. IoT based Agriculture (Ag-IoT): A detailed study on Architecture, Security and Forensics. Information Processing in Agriculture 11, 524–541.

Saggi, M.K., Jain, S. 2022. A Survey Towards Decision Support System on Smart Irrigation Scheduling Using Machine Learning approaches. Archives of Computational Methods in Engineering 29, 4455–4478.

Shafira, A., Nugraha, S., Suhendra, T. 2023. Design of Internet of Things (IoT) based Soil Moisture Monitoring System Using Solar Power in Urban Agriculture (Horticulture). In: Proceedings of the 1st International Conference on Sustainable Engineering Development and Technological Innovation, ICSEDTI 2022, 11-13 October 2022, Tanjungpinang, Indonesia. EAI.

Sreeram, R., Adithya Krishna, S., Kumar, A.S., Remya, S., Cho, Y.Y. 2026. Soil moisture monitoring technologies in smart agriculture: A comprehensive review. Farming System 4, 100189.

Syarovy, M., Nugroho, A.P., Sutiarso, L., Suwardi, Muna, M.S., Wiratmoko, A., Sukarman, Primananda, S. 2022. Utilization of Big Data in Oil Palm Plantation to Predict Production Using Artificial Neural Network Model.

Syarovy, M., Nugroho, A.P., Sutiarso, L., Suwardi, Muna, M.S., Wiratmoko, A., Sukarman, Primananda, S. 2023. Prediction of Oil Palm Production Using Recurrent Neural Network Long Short-Term Memory (RNN-LSTM). pp. 55–66.

Wiratmoko, A., Nugroho, A.P., Afif, S., Arsyad, F., Ramadhanty, M.A., Sutiarso, L. 2025. Analisis Dinamika Vapor Pressure Deficit pada Lingkungan Mikroklimat Padi Sawah Terbuka Berbasis Smart Automatic Weather Station Tipe Ultrasonik. Journal of Agricultural and Biosystem Engineering Research 6, 118.

Wiratmoko, A., Nugroho, A.P., Muna, M.S., Syarovy, M., Suwardi, Sukarman, Sutiarso, L. 2023. Development of Cloud-Based Decision Support System for Fertilizer Management - A Case Study in Wilmar Oil Palm Plantation. In: Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022). Atlantis Press.

Wiratmoko, A., Nugroho, A.P., Ramadhanty, M.A., Arsyad, F., Pradana, F.A., Pamungkas, B.S., Sutiarso, L., Okayasu, T. 2026. Predicting Physiological Health States of Tropical Papaya Using UAV Multispectral Imagery for Precision Agriculture Monitoring. Agricultural Environment and Sustainability 100023.

Zhang, X., Feng, G., Sun, X. 2024. Advanced technologies of soil moisture monitoring in precision agriculture: A Review. J. Agric. Food Res. 18, 101473.