Klasifikasi Pencari Kerja pada Disnaker Menggunakan Metode K-Means Clustering
DOI:
https://doi.org/10.47065/bulletincsr.v4i2.334Keywords:
K-Means; Clustering; Rapid Miner; Worker; ClassificationAbstract
The Manpower Office (Disnaker) is a government institution tasked with supporting, controlling, and supervising the employment sector. In addition, the Manpower Office is also responsible for providing specialized skills training to prospective employees to the needs of the job market and providing broad access to employment opportunities. This research aims to cluster job seeker data based on education level in the Medan area using the K-Means Algorithm through a clustering method approach with the application of Data Mining Techniques using RapidMiner software to obtain accurate and relevant data. The results of the implementation of the K-Means Algorithm on job seeker data in the Medan area show the formation of 6 groups (k6) with a Davies Bouldin Index (DBI) value of 0.185. This study shows that the use of cluster (k6) as the optimal k provides the best DBI value, which is 0.185, indicating the level of similarity of data in each group is getting closer.
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