Open AccessLogistics Regression Modelling on Student Career Path Choices at the Statistics Department, FMIPA UNM Makassar
Author(s) -
Muhammad Arif Tiro,
Bobby Poerwanto,
Muhammad Fahmuddin
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2123/1/012002
Subject(s) - logistic regression , artificial intelligence , computer science , algorithm , statistics , machine learning , mathematics
Survey of career path that students plan after completing their undergraduate in statistics department was carried out through questionnaire on google form from May 6 to May 24, 2021. There were 114 students who filled out the questionnaire, consisting of 20 students from class 2018, 23 students from class 2019, and 71 students from class 2020. Dependent variable is career path plan (Y), while independent variables are tendency to choose career paradigm (CPC), gender (GDR), Grade Point Average (GPA), parental occupation (POC), number of siblings (NOS), place of birth (POB) and year of university entrance (YOE). The data are analysed by binary logistic model with logit transformation and the result is g ( Y ) = ln [ π ( Y ) 1 − π ( Y ) ] = − 13 , 525 + 2 , 332 ( CPC ) − 1 , 036 ( GDR ) + 4 , 466 ( GPA ) + 2 , 421 ( POC 1 ) − 0 , 405 ( POC 2 ) + 2 , 390 ( POC 3 ) + 0 , 236 ( NOS ) − 1 , 817 ( POB ) + 0 , 448 ( YOE 1 ) − 2 , 660 ( YOE 2 ) Results of the analysis show that predictive power of the model to explain tendency of students to choose career according to statistics is around 34% to 56% based on variables in the model. Beside that tendency of career paradigm choice (CPC), Grade Point Average (GPA), parental occupation (POC1 civil servant), place of birth (POB), and year of entry (YOE 2 2019) significantly affect chosen career goals by student.