Water is a basic human need, without water humans cannot carry out activities. However, not all types of water can be consumed and are healthy for humans. So it is important to check water quality regularly. Because the influence of weather can make the water quality unfit consumption. To determine water quality, laboratory testing is required. This test requires complex analysis results so the time used in testing is relatively longer. In data mining there are classification techniques that can be used to group drinking water samples based on several variables that have been determined from water data. The aim of this research is to classify the types of drinking water that are suitable for consumption and the characteristics of healthy water. To process the data using the Naïve Bayes algorithm and produce an accuracy value of 75%.
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