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Descriptive Modeling Uses K-Means Clustering for Employee Presence Mapping

Nengsih, Warnia (2020) Descriptive Modeling Uses K-Means Clustering for Employee Presence Mapping. Mecs Press, Hongkong.

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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 kmeans clustering method. The results of the mapping obtained help the management level in controlling and monitoring
as a reference for the next policy maker.

Item Type: Other
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Jurusan Teknologi Informasi > Program Studi Sistem Informasi
Depositing User: Warnia Nengsih
Date Deposited: 02 Aug 2023 07:14
Last Modified: 02 Aug 2023 07:14
URI: http://eprints.pcr.ac.id/id/eprint/135

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