Penerapan Data Mining Klasifikasi Tingkat Pemahaman Siswa Pada Pelajaran Matematika

 (*)Tri Novika Mail (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
 Poningsih Poningsih (AMIK Tunas Bangsa, Pematangsiantar, Indonesia)
 Harly Okprana (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
 Agus Perdana Windarto (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
 Hasudungan Siahaan (STIKOM Tunas Bangsa Pematangsiantar, Indonesia)

(*) Corresponding Author

Submitted: September 15, 2020; Published: January 22, 2021

DOI: http://dx.doi.org/10.30865/mib.v5i1.2498

Abstract

The purpose of the research is to classify the concept of understanding students in Mathematics lessons. In the learning process teaching students understanding learning materials is very important. The attainment of student understanding is a function of the being of an educator. Many formulas and concepts to understand make it difficult for students to solve math problems. The data source was obtained from the results of a math comprehension questionnaire of eighth graders at Tamansiswa Tapian Dolok Private Junior High School. The classification method used is the C4.5 Algorithm and assisted with RapidMiner software. Attributes used are student interests, how students learn, student motivation, how to teach teachers, learning media, and infrastructure facilities. The results of the calculation of entropy values and attribute gains obtained 15 rules of mathematical comprehension decisions with 9 rules of understanding status and 6 rules of inconsistency status. Classification modeling with C4.5 Algorithm on RapidMiner obtained 96.00% accuracy Classification with C4.5 Algorithm can be applied and provide new information about the classification of student comprehension concepts in math lessons

Keywords


Data Mining; Classification; Algorithm C4.5; Student Comprehension; Mathematics

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