Monitoring dan Pengendalian Sistem Hidroponik Deep Flow Technique (DFT) Pada Tanaman Melon Menggunakan Metode Rule Based Berbasis Internet of Thinks

Authors

  • Ridha Teknik Informatika, Universitas Malikussaleh, Lhokseumawe, Indonesia
  • Munirul Ula Teknik Informatika, Universitas Malikussaleh, Lhokseumawe, Indonesia
  • Zara Yunizar Teknik Informatika, Universitas Malikussaleh, Lhokseumawe, Indonesia

DOI:

https://doi.org/10.55681/jige.v6i3.4158

Keywords:

Hydroponics, IoT, Rule-Based, Monitoring, Melon Cultivation

Abstract

Hydroponic cultivation offers an innovative solution to land limitations and supports sustainable agricultural practices. This study presents the design and implementation of an Internet of Things (IoT)-based monitoring and control system for melon cultivation using the Deep Flow Technique (DFT), enhanced with a rule-based decision-making method. The system integrates an ESP32 microcontroller with multiple sensors—including pH, temperature, TDS, and ultrasonic sensors—to monitor key parameters of the nutrient solution in real time. A rule-based algorithm is applied to automatically regulate system responses to environmental changes, such as imbalances in pH levels, nutrient concentration, and water height. The collected data is displayed through a web-based platform and Telegram notifications, enabling remote access and management. System functionality was tested under various simulated conditions to evaluate accuracy and responsiveness. The results demonstrate that the system effectively maintains the hydroponic environment within optimal ranges, promoting healthy melon growth. This implementation enhances efficiency in monitoring and control, and contributes to the advancement of smart farming technologies powered by IoT.

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References

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Published

2025-09-08

How to Cite

Ridha, R., Ula, M., & Yunizar, Z. (2025). Monitoring dan Pengendalian Sistem Hidroponik Deep Flow Technique (DFT) Pada Tanaman Melon Menggunakan Metode Rule Based Berbasis Internet of Thinks. Jurnal Ilmiah Global Education, 6(3), 1784–1791. https://doi.org/10.55681/jige.v6i3.4158