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Testing of Soil Moisture and Temperature Sensors in an Automatic Plant Watering System Based on the Internet of Things (IoT) Yudoyono, Susilo; Setiawan, Dewa Gede Eka; Yunus, Muhammad; Latief, Muh. Fachrul; Meidji, Icha Untari
Jurnal Pijar Mipa Vol. 20 No. 7 (2025): in Progress
Publisher : Department of Mathematics and Science Education, Faculty of Teacher Training and Education, University of Mataram. Jurnal Pijar MIPA colaborates with Perkumpulan Pendidik IPA Indonesia Wilayah Nusa Tenggara Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpm.v20i7.10585

Abstract

The implementation of automated plant watering systems in the agricultural sector utilizes sensor technology based on the Internet of Things (IoT). This study aims to evaluate the performance of soil moisture and temperature sensors utilizing the IoT in an automated plant watering system. The sensors used are the YL-69 sensor to determine soil moisture and the DS18B20 temperature sensor to determine soil temperature. Both sensors are connected to the NodeMCU ESP8266 microcontroller. Testing was conducted from 07:00 to 17:00 WITA, with a 1-hour interval for data collection, monitored using the IoT on the blink application on the cellphone. Then, the data obtained is analyzed to determine the values of error and accuracy. The results obtained on the soil moisture sensor have an average error of 0.989% with an average accuracy of 99.011%. Meanwhile, the results obtained on the soil temperature sensor have an average error of 1.240% with an average accuracy level of 98.760%. The lower the error value, the better the sensor performance indicates the sensor's ability to read data that is close to the actual value of the comparison tool. Likewise, the higher the level of sensor accuracy, the better and more reliable the sensor is when used in an IoT-based soil temperature measurement system. This value indicates that the sensor's performance has a very high level of reliability and precision in detecting soil moisture and temperature in real-time. This system can be applied in agricultural technology education and vocational training programs.