The classification of water quality is vital to ensure that the water has been properly utilized. As of today, the water treatment plant employs a conventional method by taking water sample, measuring all of water quality parameters, and analyzing each sample. Besides, the conclusion-drawing processes have not been incorporated which might lead to water quality misclassification and prolonged efforts. In this study, an expert system was developed to monitor the water quality in real time fashion, therefore it could be accessed anytime and anywhere. The water quality analysis process was conducted by means of fuzzy classifier, and implemented on Arduino Mega 2560 board. The fuzzy inputs included pH value, total dissolved solid (TDS), and turbidity. A fuzzy inference system was employed to classify the water quality into three classes, namely good (meet the hygiene standards), fair, and poor (polluted). The expert system successfully yielded the inference results with a success rate of 100%. The water quality monitoring and classification could be accessed online through Internet of Things (IoT) platform Thingspeak.