A Model Based Prediction of Desirable Applicants through Employee’s Perception of Retention and Performance
Eduardo B. Santiago & Glenn Paul P. Gara
IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), 2018
Abstract
Selecting desirable applicants for an organization who has less tendency to quit their jobs are one of the major challenges in human resource management. Proper selection during pre-employment has a significant impact in an organization’s productivity and performance. However, due to a prevalence of labor market competition, some companies are suffering to high turnover rate. It occurs when an applicant decides to quit and transfers to an organization which offers attractive benefits and compensation. This study helps human resource personnel to understand psychological climate and supports decisions in resolving employment turnover by selecting desirable applicants who has high probability of staying longer in an organization. Using the 12 dimensions of retention applied in generating association rules and naive bayes classifier, the researchers develop a custom application that can support organization’s decision in relation to hiring process. Based on the results of 12 dimensions of retention, the system evaluated seven dimensions with poor psychological climate response resulting to higher possibility of employees to voluntarily quit his or her job. Moreover, upon generating the model for job position counter cashier, results show that age older than 20 years old and living away from workplace has higher probability of staying long in comparison to other applicants. This study employs PHP-ML Library in generating association rules and classification to analyze the profile of past and current employees in the company. The results were validated using the RapidMiner software to ensure the accuracy of the implementation of association rule mining and naive bayes classifier.
BibTeX
@inproceedings{santiago2018_amodelbased,
title = {A Model Based Prediction of Desirable Applicants through Employee’s Perception of Retention and Performance},
author = {Santiago, Eduardo B. and Gara, Glenn Paul P.},
booktitle = {2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)},
year = {2018},
location = {Baguio City, Philippines},
doi = {10.1109/HNICEM.2018.8666397},
organization = {IEEE}
}
Cite
E. B. Santiago and G. P. P. Gara, "A Model Based Prediction of Desirable Applicants through Employee’s Perception of Retention and Performance," 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM), Baguio City, Philippines, 2018, pp. 1-6, doi: 10.1109/HNICEM.2018.8666397.