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LINEAR REGRESSION MODEL: A STEP ANALYSIS AND ITS APPLICATION FOR EVALUATING THE STUDENT LEARNING PROCESS IN MATH SUBJECT

Erna Kumalasari Nurnawati(1), Ismail Setiawan(2),


(1) Informatics Department, Institut Sains & Teknologi Akprind, Yogyakarta
(2) System and Information Technology, Universitas Aisyiyah, Surakarta, Central Java
Corresponding Author

Abstract


Essentially, education serves to create generations or people who are excellent thinkers, doers, and decision-makers. Based on academic performance, students' character sizes. Naturally, achieving good marks is influenced by a variety of things. The goal of this study is to examine the variables that affect student learning achievement using the linear regression method. The procedure is as follows: Convert the date to a number, eliminate any missing values, eliminate overlapping data, normalizing data (transforming a domain), Determine the correlation between the target attribute and the other attributes with the highest positive values, then select the target attribute.  According to the 9:1 ratio, divide the data into test and train data.  Find out how well the created model performs and what parameter modifications will result in the greatest performance. The calculations' findings and the developed model demonstrate that the qualities G1 (first period grade) and G2 (second period grade) are important determinants of elevating student achievement. In a comprehensive year-long learning assessment, the G2 (second period grade) attribute had the biggest influence on students' performance.

Keywords


Education, Linear Regression, Students

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DOI: 10.56327/jurnaltam.v15i1.1536

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