Drinking Water Quality Determination Information System Using AI and IOT-Based C4.5 Method - Nurkhaidah Nurkhaidah; Aa zezen Zaenal Abidin; Yuli Murdianingsih (Eduvest - Journal of Universal Studies, 2025)
The increasing consumer demand for clean water poses a challenge in maintaining the quality of refillable drinking water. One issue that is often overlooked is the cleanliness of water towers or storage tanks, which can cause the accumulation of dirt, moss, and bacteria, thereby reducing the quality of water supplied to consumers. However, there is currently no automated system capable of monitoring water quality parameters such as turbidity, Total Dissolved Solids (TDS), and water level in real time at refill depots. This study aims to utilize Internet of Things (IoT) technology and apply the C4.5 algorithm method. This research designs and builds an Internet of Things (IoT)-based information system to monitor drinking water quality in real time using ultrasonic, TDS, and turbidity sensors. The data to be calculated is data taken directly in the field using a microcontroller with ultrasonic, TDS, and turbidity sensors. The data is then processed using data mining techniques and the C4.5 algorithm method. The sensor results obtained 130 data points, of which 91 data points were used as training data and 39 data points as testing data. The C4.5 algorithm implementation was carried out with three parameters, namely water level to measure the height of water in a place, TDS to measure the Total Dissolved Solids (TDS) value or the amount of dissolved solids in water, and turbidity sensor to measure water quality by detecting its turbidity level.