Police personality classification using principle component analysis-artificial neural network
Nor Haizan Mohamed Radzi, Muhammad Sirajuddin Mazlan, Noorfa Haszlinna Mustaffa, Roselina Salleh Sallehuddin · 2017
Personality is the defining essence of an individual as it guides the way we think, act and interpret external stimuli. Classification of personality is important as it can serves as a framework in the job assignment task, particularly, in the high risk job including the Police Force. There are many attributes of individual traits but not all of them can be used to indicate individual personality. In this paper, two classification models were developed to predict individual personality for the Royal Malaysian police (RMP) based on Type A and Type B personality theory. Both classification models are based on Artificial Neural Network (ANN). But, the second model applied Principle Component Analysis or called as PCA-ANN model. The second classification model successfully reduces the number of personality features to six features compared to initial 10 features. Furthermore, PCA-ANN improves the classification accuracy to 98.6% compared to 94.4% classification accuracy found in the first ANN model.