Framework Prediksi Serapan Bekerja Alumni Berbasis Pembelajaran Mesin

Authors

  • Devi Fitrianah Mercu Buana University
  • Yuli Harwani Mercu Buana University

DOI:

https://doi.org/10.21512/emacsjournal.v2i1.6251

Keywords:

prediction framework, employability, graduates, machine learning, clustering, classfication

Abstract

Determining the employability of graduates should become the main concern of a university business in order to be able to measure the currucullum effectiveness. The university must identify the characteristics and processes in this effort to gain a knowledge in this essential information. The characteristics is utilized in the predicting framework, which is a data driven method. A machine learning approach is implemented to discover a distinguihed pattern, prediction and also mapping of students type along with the academic characteristics that is quick in the employability. This study answer the urge to have the framework based on machine learning to predict the graduates’ employability.

Dimensions

Author Biographies

Devi Fitrianah, Mercu Buana University

Teknik Informatika

Yuli Harwani, Mercu Buana University

Manajemen

References

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Published

2020-01-28

How to Cite

Fitrianah, D., & Harwani, Y. (2020). Framework Prediksi Serapan Bekerja Alumni Berbasis Pembelajaran Mesin. Engineering, MAthematics and Computer Science Journal (EMACS), 2(1), 21–28. https://doi.org/10.21512/emacsjournal.v2i1.6251

Issue

Vol. 2 No. 1 (2020): EMACS

Section

Articles

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Copyright (c) 2020 Devi Fitrianah, Yuli Harwani

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