INFORMATION CHANGE THE WORLD

International Journal of Information Engineering and Electronic Business(IJIEEB)

ISSN: 2074-9023 (Print), ISSN: 2074-9031 (Online)

Published By: MECS Press

IJIEEB Vol.12, No.4, Aug. 2020

Descriptive Modeling Uses K-Means Clustering for Employee Presence Mapping

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Author(s)

Warnia Nengsih, Muhammad Mahrus Zain

Index Terms

Descriptive Modelling, K-Means, Clustering

Abstract

Human resource is valuable asset for an agency. The success of an institution is not only determined by the quality of its human resources, but also by the level of discipline. The discipline of an employee in an institution can be seen and measured by the level of attendance in doing a job, because the level of attendance is one of the factors that determine productivity. The current problem is the management level of the company that has difficulty in monitoring and controlling the employee attendance data. There needs to be a mapping and grouping to find out patterns of absence. Mapping or patterns that are obtained help management levels to monitor employees, take approaches and take action so as to improve employee discipline. In this study, it was used descriptive modeling with the implementation of the k-means clustering method. The results of the mapping obtained help the management level in controlling and monitoring as a reference for the next policy maker.

Cite This Paper

Warnia Nengsih, Muhammad Mahrus Zain, " Descriptive Modeling Uses K-Means Clustering for Employee Presence Mapping", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.12, No.4, pp. 15-20, 2020. DOI: 10.5815/ijieeb.2020.04.02

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