Path Analysis to Determine the Effect of Learning Outcomes of Prerequisite Mathematics on Expert Systems Courses

Abstract

The study background is the need to evaluate learning and the placement of the sequence of courses. The learning objectives are achieved optimally. This study conducts a path analysis to determine the direct or indirect effect of learning outcomes for mathematics prerequisite courses, Discrete Mathematics and Linear Algebra and Matrix, on learning outcomes of Expert Systems with Artificial Intelligence as an intervening variable. This study is explanatory research conducted at the Study Program of Informatics Engineering, STMIK Palangkaraya. The sample used is the 2017 and 2018 batch of students who have taken and passed the MD, AL, KB, and SP courses, as many as 94 people. The data were analyzed using student learning outcomes in the four courses. The data were then selected and analyzed descriptively, the assumption of path analysis (normality, multicollinearity, and heteroscedasticity) was tested, and finally, path analysis was performed. Hypothesis testing was carried out with the help of the R program. The results showed (1) the learning outcomes of the MD and AL courses directly significantly affected the learning outcomes of the KB courses by 23% and 23.7%, respectively, and (2) the learning outcomes of the AL courses directly affected the learning outcomes of the SP courses by 34.9%, (3) the learning outcomes for MD and KB courses do not directly affect learning outcomes for SP courses, (4) learning outcomes for MD and AL courses do not indirectly affect learning outcomes for SP courses.