PT PLN (Persero) WS2JB Rayon Kayu Agung have a big desire to apply a Knowledge Management System. KMS will have a positive effect to the quality of employees. Where each employee can save, documentating and sharing their knowledge, and find it in the database with features of searching. In this case, KMS will be combined with Knowledge Data Discovery(KDD) techniques to explore and seek knowledge electricity bill data as one of the new explicit knowledge. The methodology used in this study refers to the KM methodology that was developed by Amrit Tiwana (1999) and KDD (Fayad, 1996) techniques using Algorithm of C4.5 . With source data derived from the payment data and customer data obtained factors that affect customers in paying utility bills. The results can provide a new knowledge to predict customer bill payment for the next month. So PLN can use it as one of the decision makers in the electricity arrears problem. The system web based will use programming language PHP and Weka as processing applications of data mining.