Ordinal logistic regression model on the level of job relevance of graduates - Sunanto, Rahma Faelasofi; Nisa, Khoirin (Universitas Islam Negeri Raden Intan Lampung, 2023)
The ordinal logistic regression model is one of the statistical models used to classify ordinal data. The purpose of this study is to identify the relevance of FKIP Muhammadiyah Pringsewu University Lampung graduates. The population in this study were FKIP Muhammadiyah Pringsewu University Lampung graduates in three academic years from 2018-2021. The total of the sample in this study was 133 graduates. There was missing data that was classified as Missing Random (MAR). The ordinal logistic regression model used an odds proportion model. This study will analyze the relationship between the response variable is the relevance of the graduate's work according to the field of work that has three classifications high, medium, and low, against the nine predictor variables predicted affecting the predictor variable. The result of the data description available stated that 80.3% of graduates had a high level of job relevance, 11.4% of graduates had a moderate level of job, and 8.3% of graduates had a low level of job relevance. Then the result of the ordinal logistic regression model using the proportional odds model showed that the variable predictor IPK graduates with categories 3.01-3.50; 3.406; and 3.51-4.00, predictor variable of looking for or getting a job either before or after, and variables predictor types of permanent jobs give a significant influence on the level of job relevance of graduates.