The application of particle swarm optimization using neural network to optimize classification of employee performance assessment
Mohammad Humam, Oman Somantri, Maylane Boni Abdillah, Syaefani Arif Romadhon, Mohammad Khambali, Robbi Rahim · Journal of Physics Conference Series · 2019
The measurement of employee value performance in an institution is very important for the future evaluation and planning. The employee performance assessment absolutely must be done to determine the accomplishments to be achieved by every employee. Policy makers are difficult to determine the optimal classification toward assessment of the performance appraisal. Selection of the best attributes weights in optimizing Neural Network for the performance appraisal that has been not optimal yet and the effect on level of accuracy that is generated. Practitioners of Particle Swarm Optimization (PSO) on Neural Network (NN) are expected to optimize the selection of the best attribute weights to the performance appraisal classification resulting in increased accuracy.