Implementasi Sistem Monitoring Kualitas Air Berbasis Internet of Things dengan Multisensor

Abstract

Continuous monitoring of household borewell water quality is essential for the early detection of changes in water conditions. This study develops and evaluates a laboratory-scale prototype of an Internet of Things (IoT)-based monitoring system for early water condition indicators, utilizing a TDS sensor (SEN0244) and a temperature sensor (DS18B20) connected to an ESP8266 microcontroller. The prototype was tested using a plastic bucket filled with borewell water to simulate a household water storage system. Measurement data were transmitted via the HTTP protocol to a Flask server, stored in an SQLite database, and displayed on a web-based dashboard in near real-time. The Sugeno fuzzy logic method was implemented to provide a more stable and gradual interpretation of water conditions based on TDS values as the primary indicator and temperature as a supporting parameter, in accordance with the Indonesian Ministry of Health Regulation (Permenkes RI) Number 2 of 2023. The experimental results showed an average accuracy of 97.76% for the TDS sensor and 98.59% for the temperature sensor. Black-box testing achieved a 100% success rate (19/19 test scenarios), while data transmission was successful in 100% of cases under normal network conditions. One-day monitoring produced 180 valid data records, with TDS values ranging from 106.47 to 116.51 mg/L, all of which complied with the water quality standards specified in Permenkes RI Number 2 of 2023. These findings are consistent with the characteristics of borewell water in rural areas of Tabanan, which were not exposed to significant contamination during the observation period. This study provides empirical evidence of the feasibility of integrating Sugeno fuzzy logic into an IoT-based monitoring system architecture using TDS and temperature measurements as a foundation for the development of similar systems at a full implementation scale.