Detecting Unethical Practices in Consuming Water by Using Data Mining Based Model

Abstract

In water, fraudulent behavior is a problem faced by companies that supply water. This act ends in a bulk amount of loss of income and creates chaos. In recent years, Researches are being made for efficient measurements to detect fraudulent activities. There are classification techniques such as SVM and KNN which is explore in the paper to detect mistrustful customers. The research’s only purpose is assisting the Nalco water company (NWC) in Jordan city for overcoming the profit loss. It finds a rate over 74% which predicts the NWC’s manual procedure. To deploy the model, we are using a decision tool to generate the model. This project will help to predict water customers who are frauds or suspicious on the site.