Sistem Pengukuran pH, Suhu, dan Kelembaban Tanah Pada Tanaman Jagung Menggunakan Metode Proportional-Integral-Derivative Berbasis Internet of things - Mira, Mira; Kusnanto, Kusnanto; Oscarito, Oscarito (Forum Kerjasama Pendidikan Tinggi, 2024)
West Kalimantan Province experienced a decrease in the harvested area and productivity of corn with an area of 16,371.14 in 2022 with a productivity of 43.81 and a production of 71,717.14 tons. While in 2023 with an area of 15,625.22 with a productivity of 43.54 and a production of 68,028.76 tons. The decline in corn production and the increasing consumption needs every year are challenges for the government and corn farming businesses to answer and meet the availability of corn. Regarding this problem, it is necessary to manage corn plantation land, in order to increase the value of corn production to meet consumption and animal feed needs in West Kalimantan. Measuring pH, temperature and soil moisture is very important to understand the right soil conditions for various types of plants. This study uses a DS18B20 sensor to measure soil temperature, capaltive soil moisture to measure air content in the soil, and a pH sensor to determine the acidity level. The ESP32 microcontroller is used as the main controller connected to the third sensor with IoT technology and the PID method as a control system. The PID constant value was determined using the Ziegler-Nichols method, with a Kp value of 4.31, Ki 0.85, and Kd 4.33 with a setpoint of ph 6.0, a temperature of 26°C and a humidity of 70%. The results showed that the pH value was in the range of 3.03-3.45, falling into the acidic category. Furthermore, the temperature value was at 24.69-28.66, falling into the medium to high category. While the humidity value was between 43-80, falling into the low to high category. The test results showed that the system was able to measure temperature, humidity, and soil pH in real-time with a good level of accuracy. This is supported by the accuracy value of the soil pH sensor of 60.6%, the temperature sensor of 98.65%, and the soil moisture sensor of 98.57%. The accuracy value is obtained from 100% minus the average error value for each measurement.