Analisis Dampak dan Tantangan Pemanfaatan Sensor Kelembaban Tanah dalam sistem Irigasi Otomatis Berbasis IoT di Sektor Pertanian Indonesia

Rudi Pramana; Affan Mahdi  Pinandito; Tedy  Septiana; Moch. Syafri  Syamsudin

doi:10.62048/qjms.v3i1.124

Authors

Rudi Pramana Program Studi Teknik Informatika dan Komputer, Institut Prima Bangsa, Cirebon, Indonesia
Affan Mahdi Pinandito Program Studi Teknik Informatika dan Komputer, Institut Prima Bangsa, Cirebon, Indonesia
Tedy Septiana Program Studi Teknik Informatika dan Komputer, Institut Prima Bangsa, Cirebon, Indonesia
Moch. Syafri Syamsudin Program Studi Teknik Informatika dan Komputer, Institut Prima Bangsa, Cirebon, Indonesia

DOI:

https://doi.org/10.62048/qjms.v3i1.124

Keywords:

internet of thing, smart agriculture, soil moisture sensor, colloidal, environmental monitoring

Abstract

Water-use efficiency remains a major challenge in Indonesian agriculture, particularly due to climate uncertainty and limited resources. The application of Internet of Things (IoT) technology offers opportunities to support data-driven decision-making through real-time environmental monitoring. This study aims to design, develop, and test an IoT-based agricultural environmental monitoring system that focuses on soil moisture measurement as a basis for water management. The research methods include system architecture design, development of ESP8266 microcontroller firmware, integration of soil moisture sensors, a BH1750 light sensor, and a DHT22 temperature and humidity sensor, as well as the development of a cloud-based visualization application using Kodular. The system was evaluated through functional testing, connectivity stability assessment, and data consistency analysis. The results indicate that the system is capable of collecting and transmitting environmental data accurately, consistently, and in real time with a high level of connection reliability. The application presents data intuitively and provides notifications for critical conditions without relying on automatic irrigation. Consequently, this system has the potential to improve water management efficiency and support more precise decision-based smart farming practices, while also serving as a foundation for the future development of sustainable automatic irrigation systems

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