Klasifikasi Tingkat Pemahaman Siswa pada Pelajaran Matematika di MTSS PAB 5 Klambir Lima

According to academic data, student math ability tests at MTSS PAB 5 Klambir Lima yield mixed results. There are students who understand math well, but there are also those who have difficulty understanding the mathematical concepts themselves. Math teachers at this school have difficulty designing lessons that can meet the needs of students with different levels of understanding. So, it is necessary to group student data to produce educational decision-making and improve learning effectiveness, such as through data mining. Data mining is a semi-automated process that uses machine learning techniques, mathematics, statistics, and artificial intelligence to identify and organize information contained in large databases. The process of finding information can be done by determining the decision rule based based on the level of student understanding in mathematics lessons using the Decision Tree Algorithm C4.5 method. The use of the Decision Tree algorithm C4.5 aims to make it easier to determine decision rules based on gender, Predicate, teacher teaching methods, student learning interest, and level of understanding. Based on the results of the study, it was found that if the teacher's teaching method is good, the predicate value is B, the student's learning interest is less interested, and the gender is male, then the student's level of understanding in mathematics lessons is not understood.

Authors

Publication Details

Journal
Saturnus
Published
2024-08-19
DOI
https://doi.org/10.61132/saturnus.v2i4.345
Primary Topic
Mathematics Education and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
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article

Klasifikasi Tingkat Pemahaman Siswa pada Pelajaran Matematika di MTSS PAB 5 Klambir Lima

Juliana Naftali Sitompul, Relita Buaton, Auni Patrisyah
Saturnus
Mathematics Education and Pedagogy
article

Klasifikasi Tingkat Pemahaman Siswa pada Pelajaran Matematika di MTSS PAB 5 Klambir Lima

Juliana Naftali Sitompul, Relita Buaton, Auni Patrisyah
article en

Abstract

According to academic data, student math ability tests at MTSS PAB 5 Klambir Lima yield mixed results. There are students who understand math well, but there are also those who have difficulty understanding the mathematical concepts themselves. Math teachers at this school have difficulty designing lessons that can meet the needs of students with different levels of understanding. So, it is necessary to group student data to produce educational decision-making and improve learning effectiveness, such as through data mining. Data mining is a semi-automated process that uses machine learning techniques, mathematics, statistics, and artificial intelligence to identify and organize information contained in large databases. The process of finding information can be done by determining the decision rule based based on the level of student understanding in mathematics lessons using the Decision Tree Algorithm C4.5 method. The use of the Decision Tree algorithm C4.5 aims to make it easier to determine decision rules based on gender, Predicate, teacher teaching methods, student learning interest, and level of understanding. Based on the results of the study, it was found that if the teacher's teaching method is good, the predicate value is B, the student's learning interest is less interested, and the gender is male, then the student's level of understanding in mathematics lessons is not understood.

SaturnusVol. 2(4)
Openalex Percentile: Top 67%
Mathematics Education and Pedagogy
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