A decision support system based on support vector machine for employee recruitment

The increase of job competition is a challenge for job seekers as well as for organizations to find and retain the right and competitive people. Inadequate recruitment processes will result in lower productivity and turnover. Therefore the organization needs an accurate decision support system to ge...

Full description

Saved in:
Bibliographic Details
Main Authors: Masruroh, Fitriana, Surarso, Bayu, Warsito, Budi
Format: Conference Proceeding
Language:English
Subjects:
Business competition
Classification
Decision support systems
Kernel functions
Polynomials
Recruitment
Support vector machines
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The increase of job competition is a challenge for job seekers as well as for organizations to find and retain the right and competitive people. Inadequate recruitment processes will result in lower productivity and turnover. Therefore the organization needs an accurate decision support system to get employees who match the qualifications of the organization. This study aims to design support vector machine (SVM) -based decision support for employee recruitment. The data used are 400 data which are divided into two classes, namely accepted and not accepted. The use of different kernel functions in the design of the SVM classification model shows that the polynomial kernel function is based on the experimental parameter value C is 23, d is 5 and the ratio experiment of 80% and 20%, the accuracy is 97.50% and the AUC is 0.99. The results of this study indicate that the designed classification model has a good performance in employee recruitment.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0109462