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All Journal Variance : Journal of Statistics and Its Applications
Faizah Sari
Business Mathematics, School of Applied STEM, Universitas Prasetiya Mulya
Mathematics

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WORKFORCE GROUPING IN COMPLETING PROJECTS WITH INTERN WORK ACTIVITY LOG DATA Brandon Anggawidjaja; Faizah Sari; Ahmad Fuad Zainuddin
VARIANCE: Journal of Statistics and Its Applications Vol 5 No 2 (2023): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol5iss2page131-138

Abstract

This study consists of an attempt to optimize the K-Means Clustering Algorithm and calculating the Full Time Equivalent (FTE) of each cluster based on intern's daily work log data. The optimization will be done by using some of K-Means Clustering’s validation method to estimate the best K clusters of the data. The validation methods that will be used to optimize the algorithm are Elbow Criterion Method and Silhouette Score Index. The initial k cluster will be formed and evaluated using Davies Bouldin Index analysis. The divided clusters are supposed to be classified by the rate of complexity of each project. The calculated FTE will be used to estimate the workload for the current workforce. This estimation is hoped to help companies decide in their hiring decision.
Co-Authors Ahmad Fuad Zainuddin Brandon Anggawidjaja