Analysis of Entrance Test Results Effect on Student's Performance using Multiple Linear Regression

The entrance selection test is the starting gate to find out the ability of prospective students. Student performance, measured by the Academic Achievement Index and the length of study, are two factors that measure the quality of a department or faculty. Therefore, it is necessary to analyze the effect of the entrance test results on student performance. The Faculty of Computer Science at Brawijaya University has various types of tests that prospective students must take in order to be accepted into the Computer Science Master's Program. Broadly speaking, these types of tests consist of Interview Tests, Academic Potential Tests, TOEFL Tests, Field Ability Tests, Psychological Tests, and S1 GPA. Regression analysis using the Multiple Linear Regression method is applied in the first 4 semesters of lectures. Tests conducted on the regression model resulted in a Mean Square Error value of 0.0321 in the first semester, 0.0273 in the second semester, 0.015 in the third semester, and 0.031 in the fourth semester, and 1.5301 for the graduation semester. While the K- Fold Cross Validation score resulted in a score of -0.044 in the 1st semester, 0.2838 in the second semester, 0.9037 in the third semester, and 0.9011 in the fourth semester, and -0.2786 in the graduation semester. In addition, dashboard visualization gets an average score of 68.33, which means it can be accepted and can be used by the Academic Team for the Master's Program in Computer Science at Brawijaya University.