Descriptive Modeling Uses K-Means Clustering for Employee Presence Mapping
Автор: Warnia Nengsih, Muhammad Mahrus Zain
Журнал: International Journal of Information Engineering and Electronic Business @ijieeb
Статья в выпуске: 4 vol.12, 2020 года.
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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.
Descriptive Modelling, K-Means, Clustering
Короткий адрес: https://sciup.org/15017408
IDR: 15017408 | DOI: 10.5815/ijieeb.2020.04.02
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