Pemodelan Regresi Logistik Biner dan Ordinal Pada Proses Seleksi Mahasiswa Baru Program D3KPLN PENS

• Ronny Susetyoko Politeknik Elektronika Negeri Surabaya (PENS)
Keywords: Binary Logistic Regression, Ordinal Logistic Regression, selection process

Abstract

Starting in 2016, Politeknik Elektronika Negeri Surabaya (PENS) accept new students D3KPLN. D3KPLN scheme is a joint program between PENS with PT. PLN
(Persero) as a form of link and match between higher education and industry needs. In the program, student candidates must go through five stages of selection, namely: academic potential test (stage-1), psychotest (stage-2), physical test (stage-3), medical tests (stage 4), and interview ( stage-5). To know the probability characteristics of the selection process generally used ordinal logistic regression model. As for knowing the accepted probability characteristics at each stage of selection used binary logistic regression model. Based on testing at each stage, the academic potential test scores are not the only determinants of acceptance as a student D3KPLN. However, other factors such as physical condition, medical test results, and interviews were also decisive. In general, the
academic potential test scores significantly affect the results of the selection phase by phase (phase-1 until phase-5). Binary logistic regression model of the final stage is = exp (-4.788 + 0.02127 Score) / (1 + (exp (-4.788 + 0.02127 Score)). This indicates that an increase of one score of the academic potential test increases probability of the applicants be accepted as student to 1.0215 times. The results of this modeling can be used as a reference to determine the passing grade in selection process next year.

References

 Murdifi, A., Berdayakan Putra Putri Terbaik Bangsa, PLN Jalin Kerjasama dengan Perguruan Tinggi. 20 Agustus 2016. http://www.pln.co.id/2016/03.

 __________, Informasi Penerimaan Mahasiswa Baru PENS. 20 Agustus 2016. http://pln.pens.ac.id/

 Anggraeni, Y., dan I. Zain. (2015). Pemodelan Regresi Logistik Biner terhadap Peminat ITS di Seleksi Bersama Masuk Perguruan Tinggi Negeri (SBMPTN) 2014. Jurnal Sains dan Seni ITS Vol. 4, No. 1, 2337-3520.

 Imaslihkah, S., M. Ratna, dan V. Ratnasari (2013). Analisis Regresi Logistik Ordinal terhadap Faktor-faktor yang Mempengaruhi Predikat Kelulusan Mahasiswa S1 di ITS Surabaya. Jurnal Sains Dan Seni POMITS Vol. 2, No. 2,
(2013) ISSN: 2337-3520.

 Hosmer, D. W., & Lemeshow, S. (2000). Applied Logistic Regression. USA: John Wiley & Sons.

 Agresti, A. (2002). Categorical Data Analysis. New York: John Wiley & Sons.
Published
2018-02-15
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