The Implementation of K-Means Algorithm to Analyse the Level of Employee Job Satisfaction Using Laravel Framework

Authors

  • Harni Kusniyati  Faculty of Computer Science, Mercu Buana University, West Jakarta, Indonesia

DOI:

https://doi.org//10.32628/CSEIT206129

Keywords:

One on one, Cluster, K-Means, Job Satisfaction, Framework, Laravel

Abstract

Every company needs to know the level of job satisfaction of their employees that can be used as suggestion and critics to help consider the way to manage their human resources. It aims to encourage their employees to work optimally. One of the ways to find out the level of employee job satisfaction is by conducting one on one (face-to-face meeting between boss and employee) to get information about job satisfaction in terms of workload, work environment, team relationship, and other aspects. The information given to HRD and top manager is then used as consideration for the company to increase the human resource management. For time efficiency, it is made an application using Laravel framework that implements K-Means algorithm. In this case, the implementation of K-Means algorithm becomes a solution by analyzing data of employee job satisfaction in the company. The result of calculation process of K-Means algorithm forms a cluster used to obtain the description of the level of employee job satisfaction toward policies in the company.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2020-02-25

Issue

Volume 6, Issue 1, January-February-2020

Section

Research Articles

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Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Harni Kusniyati, " The Implementation of K-Means Algorithm to Analyse the Level of Employee Job Satisfaction Using Laravel Framework, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 1, pp.152-158, January-February-2020. Available at doi : https://doi.org/10.32628/CSEIT206129