PROTOTYPE MONITORING NUTRISI DAN PH AIR TANAMAN HIDROPONIK BERBASIS ANDROID

Abstrak

This research discusses the challenges of manual monitoring in hydroponics, which often faces challenges in detecting nutrient parameters and water pH, which can hinder optimal plant growth. Manual monitoring proves ineffective for remote monitoring, especially for hydroponic farmers with high mobility. This research aims to design and test a prototype Android based nutrient and water pH monitoring system for lettuce cultivation using the Deep Flow Technique (DFT). The prototype system utilizes NodeMCU ESP32 as the controller for TDS sensor, pH 4502C sensor, water temperature DS18B20 sensor, as well as air temperature and humidity DHT22 sensor. Data is transmitted to Firebase Realtime Database and displayed on an LCD 16 × 2 and an Android application. Four peristaltic pumps are employed to automatically add AB Mix nutrients and pH balancing fluids based on user defined targets. Sensor accuracy is assessed using Mean Absolute Percentage Error (MAPE) method, and the Android application is tested using black box testing. The results show that the TDS sensor has an average error percentage of 6.86% and the pH 4502C sensor has an average error of 2.51%. The prototype system successfully monitors and displays data in realtime and automates the adjustment of nutrient concentration (ppm). However, the automatic control of pH levels was not successfully implemented due to unstable voltage readings.

Keywords: Hydroponics, Android, Internet of Things, Deep Flow Technique, MAPE, Black Box Testing