Xplore: Journal of Statistics
Vol. 10 No. 2 (2021)

Penerapan Regresi Logistik Biner Multilevel terhadap Ketepatan Waktu Lulus Mahasiswa Program Magister Sekolah Pascasarjana IPB

Zana Aprillia (Department of Statistics, IPB)
Farit Mochamad Afendi (Department of Statistics, IPB)
Akbar Rizki (Department of Statistics, IPB)



Article Info

Publish Date
31 May 2021

Abstract

The study length of alumnus is one of the study achievement indicator of the university. Study length for Master Program can be divided into two categories which is pass on time (study length ≤24 months) and pass not on time (study length >24 months). In the classical regression analysis, each student are assumed to be independent. But in reality, each student are grouped into a different study programs so that the individuals who are in the same study program tend to have a similar characteristics. Multilevel regression is one of the analysis that accomodates the problem. The level used in this study are level 1 (individual student) and level 2 (study programs). The best multilevel regression model obtained is a model with random intercept and the variance is produced from study program is 0.6636. Factors that give an effect to the graduation’s timeliness are age, married status, and the source of the S2 education cost.

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Journal Info

Abbrev

xplore

Publisher

Subject

Decision Sciences, Operations Research & Management Engineering Mathematics

Description

Xplore: Journal of Statistics diterbitkan berkala 3 (tiga) kali dalam setahun yang memuat tulisan ilmiah yang berhubungan dengan bidang statistika. Artikel yang dimuat berupa hasil penelitian atau kajian pustaka dalam bidang statistika dan atau penerapannya. ISSN: 2302-5751 Mulai Desember 2018, ...