Personnel Audit Using a Forensic Mining Technique
This paper applies forensic data mining to determine the true status of employees and thereafter provide useful evidences for proper administration of administrative rules in a Typical Nigerian Teaching Service. The conventional technique of personnel audit was studied and a new technique for personnel audit was modeled using Artificial Neural Networks and Decision Tree algorithms. Atwo-layer classifier architecture was modeled. The outcome of the experiment proved that Radial Basis Function Artificial Neural Network is better than Feed-forward Multilayer Perceptron in modeling of appointment and promotion audit in layer 1 while Logitboost Multiclass Alternating Decision Tree in Layer 2 is best in modeling suspicious appointment audit and abnormal promotion audit among the tested Decision Trees. The evidential rules derived from the decision trees for determining the suspicious appointment and abnormal promotion were also presented.
Keywords: Data Mining, Forensic, Audit, Appointment, Promotion
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