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Ikasakti, Nur Aini
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Computer Science & IT Social Sciences

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Job applicants clustering using self-organizing map Primandari, Arum Handini; Ikasakti, Nur Aini
Bulletin of Social Informatics Theory and Application Vol. 1 No. 2 (2017)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v1i2.28

Abstract

Yogyakarta Government through Directorate of Manpower and Transmigration (Disnakertrans) have been canvassing people looking for job. An employment program was provided by Disnakertrans to allow job applicants meet companies. This research was carried out to identify educational background of applicants, in order to obtain the suitable worker. One of the ways to identify educational background is by district clustering in Yogyakarta. Clustering method is employed to reveal the characteristic of educational quality in every district in Yogyakarta. Clustering is a grouping method which is done by minimalize the characteristic among class members and minimalize the characteristic among clusters. This research used Self Organizing Maps to grouping districts in Yogyakarta according to educational background of its job seekers. The clustering results 3 clusters: 6 districts belong to cluster 1, 4 districts belong to cluster 2, and 4 districts belong to cluster 3. Then, Yogyakarta map is used to visualize the result of district clustering.
Co-Authors Primandari, Arum Handini