Sistem Deteksi Kualitas Air Minum Menggunakan Sensor PH, Dissolved Oxygen, Konduktivitas dan Suhu Berbasis Mikrokontroler ESP32

Abstract

Water is a natural resource that is important for human life. The availability of clean water for consumption is generally a very primary issue because various diseases that arise due to poor water quality are unknown to the general public. The diversity of water sources is an obstacle due to the lack of availability of water quality detection tools. Water samples for testing were collected from one of the wells. Water can be said to be of quality if it meets several requirements in accordance with the Regulation of the Minister of Health of the Republic of Indonesia No.492/MENKES/PER/IV/2010 and Minister of Health Regulation No.2 of 2023, including temperature (±3°C from the air temperature where the water is located) , pH (6.5-8.5), conductivity (42-500 μS/cm) and TDS (<300 ppm). The input sensors used in this research are pH sensors, TDS sensors, conductivity sensors, and DS18B20 sensors. The results of the measurement tools made were compared with the results of SNI measuring tools, namely pH meters, TDS meters, digital thermometers, and laboratory results. Then, the measurement results from the sample have good temperature quality (27.4°C), good pH (7.8), and good TDS (203 ppm) but with conductivity values that are not included in the scope of SNI ISO/IEC accreditation 17025:2017 (518.8 μS/cm ). Input from the sensor is processed by the ESP32 microcontroller and the results will be displayed on the LCD, and on the smartphone with the Virtuino application in real- time. Apart from that, this system can also help the government or related institutions in monitoring and taking quick action on changes in well water quality. This tool can be used with high data accuracy, data consistency and durability for measuring water quality. The results of this research showed that the drinking water quality detection system based on the ESP32 microcontroller had a very good accuracy of 97.5% on average. With this it can be concluded that this tool is very effective when used to detect the quality of drinking water.