Discriminant Analysis of Factors Affecting the Grade Point Average (GPA) of Mathematics Education Students Maria Elfantiana Senia (a*), Patrisius Afrisno Udil (b), Christine Krishnandari Ekowati (c)
Department of Mathematics Education, Faculty of Teacher Training and Education, Universitas Nusa Cendana
Adi Sucipto st., Penfui, Kupang 85001, Indonesia
Abstract
Students^ Grade Point Average (GPA) represents the quality of students learning process and achievement. However, the low and fluctuating students^ GPA is still a problem that is often encountered among university students. So, it is necessary to examine the factors that cause this through discriminant analysis. This study aimed to determine discriminant model of factors affecting students^ GPA. It was also aimed to know what factors have a significant effect on the GPA of mathematics education students in Nusa Cendana University. The population of this research is all active students of class 2018, 2019, and 2020 in mathematics education program, Nusa Cendana University. The sample consists of 100 students which were taken using simple random sampling technique. This research is a quantitative research with survey method. The instruments used consisted of three main instruments of selected factors namely 1) an open questionnaire related to the factors of study time, pocket money, and sleep time, 2) an organizational activity questionnaire, and 3) a learning motivation questionnaire. Meanwhile, data related to student GPAs were obtained from the academic section of the mathematics education study program at Nusa Cendana University. Discriminant analysis with SPSS 24 was used to analyze the data obtained. The results of the study found that the discriminant function/model of the factors that affect student GPA is Y= 8.854768 + 0.530341 X1 + 0.404140 X2 + 0.905366 X4 +1.056100 X5. Furthermore, it was also found that the variables of learning motivation (X5), organizational activity (X4), pocket money (X2), and study time (X1) were factors that significantly influenced the GPA of mathematics education students with the accuracy of classifying the discriminant function is 72%.
Keywords: Discriminant Analysis- GPA- Learning Motivation- Organizational Activity- Pocket Money- Study Time
