Professional Clustering Based on the Graduates Profile Using K-Means Method

PIKSEL (Penelitian Ilmu Komputer Sistem Embedded dan Logic)

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Title Professional Clustering Based on the Graduates Profile Using K-Means Method
Creator Susi, Susi
Hajjah, Alyauma
Description The Information Systems department of Pelita Indonesia Institute of Business and Technology produces graduates with education knowledge to face the professional work, but the majority of students after graduating do not work according to their graduate profiles/educational background. This research aimed to help students in determining the appropriate graduate profile. The proposed system was built using the K-means method for the classification process of graduate profiles; hence, the results can be used as recommended profession to be taken. The data used in this study is the data of students of class 2016, and these results are compared with their current professional record data with the aim of knowing the percentage of professional suitability obtained with the current profession. After this research is tested, the results of the classification of the graduate profile can be obtained where there are 10 students in the administrator database cluster, 11 students of the web design and developer cluster, one student of the cluster information system manager, and 8 students of the cluster system analysis. The percentage of suitability was 43.33%. This program is designed using the PHP programming language.
Publisher LPPM Universitas Islam 45 Bekasi
Date 2021-03-24
Type info:eu-repo/semantics/article
Format application/pdf
Source PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic; Vol 9 No 1 (2021): Maret 2021; 75 - 88
Language eng
Rights Copyright (c) 2021 PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic

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