Analysis of the Effectiveness of Employee Training Programs Using K-Means Algorithm Based on RapidMiner in an Industrial Catering Company in Jakarta

Gonggo Prio Trilaksono; Arief Wibowo

doi:10.63922/ijebir.v5i04.4463

Gonggo Prio Trilaksono Master of Management Student, Budi Luhur University
Arief Wibowo Professor of Intelligent Systems for Crisis & Disaster Management, Budi Luhur University

DOI: https://doi.org/10.63922/ijebir.v5i04.4463

Keywords: Cluster Analysis, K-Means, RapidMiner, Training Effectiveness, Industrial Catering.

Abstract

This study aims to measure the effectiveness of employee training programs in an industrial catering company in Jakarta based on the variables of work tenure and job position. The analytical method used is computational data mining with the K-Means Clustering algorithm through RapidMiner software. The evaluation for determining the optimal number of clusters is based on the Davies-Bouldin Index (DBI) testing. The results show that the configuration of three clusters (K=3) is the best model for both operational units, with DBI values of 0.671 for the Hospital unit and 0.636 for the Factory unit. This segmentation successfully mapped employee characteristics into three levels of effectiveness: "Excellent", "Good", and "Fair". It was found that in the Factory unit, the highest training effectiveness was achieved by employees with mid-level tenure at the basic operational level. Meanwhile, in the Hospital unit, the best performance was dominated by senior employees at the mid-to-lower job position scale. Managerially, the clustering results provide an objective foundation for the company in formulating personalized, targeted, and actual-data-based human resource development strategies.

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