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ABSTRACT
The provision of technology with electric power and diverse usage in different electronic household appliances was distributed to customers being produced from transmission line. Resident with energy consumption in household appliance often engage in energy theft; Since energy theft is a general problem across nations. Prepaid metering system was introduced with no adequate outcome to minimize power theft. This project work aimed to investigate the rate of energy theft in a residential household appliance consumption. In order to achieve this, a quantitative and descriptive analysis was used to train and test the dataset in determining the percentage accuracy of power theft prediction, the combination of Artificial Neural Network and fuzzy logic method was used to demonstrate this dataset. The results show various rate of detecting energy theft as it relates to the relationship between Expected units and Actual units in prepaid metering system. This propose Artificial Neural Network and Fuzzy Inference system (ANFIS) model provide better prediction percentage accuracy in detecting energy theft in a residential household appliance energy consumption rate in electrification.
