PENERAPAN PARTICLE SWARM OPTIMIZATION PADA ALGORITMA C 4.5 UNTUK SELEKSI PENERIMAAN KARYAWAN

Abstract

The Employees are the most vital element of the company as they had a big contribution and involved almost for all section on how the company will go up and down. Employees and the company affect the efficiency, effectiveness,
designing, producing goods and services, oversee the quality, market products, allocating financial resources, and determines the overall goals and strategies of the organization. Therefore, organizations need accurate information and sustainable in order to get suitable candidates with the qualifications of the organization. Model algorithms are widely used in research related to the employee is C4.5 decision tree classification model. Advantages of using a
decision tree classification models are the result of the decision tree is simple and easy to understand. Many studies using the method of decision tree and classification tree in predicting the employees selection but results the
accuracy of the resulting value is less accurate. In this study created a C 4.5 Algorithm model and C 4.5 Algorithm model based on particle swarm optimization to get the rule in employees selection and provide a more accurate
value of accuracy. After testing C 4.5 algorithm model based on particle swarm optimization, Implementation of particle swarm optimization can produce accuracy value of C 4.5 algorithm model from 80.80 % to 85.20 % and the
AUC value from 0.878 to 0.891. By the formation the model selection of employees, the company can be helped for employee selection.