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All Journal Mathvision : Jurnal Matematika
Siti Aisyah
Universitas Pamulang
Mathematics

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KLASIFIKASI TINGKATAN LEVEL KUMON DENGAN MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Siti Aisyah; Nina Valentika; Aden Aden
MathVisioN Vol 4 No 1 (2022): Maret 2022
Publisher : Prodi Matematika FMIPA Unirow Tuban

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (173.557 KB) | DOI: 10.55719/mv.v4i1.305

Abstract

Kumon is a tutoring place that implements a level-based learning system customized to individual abilities, aims to optimize each individual's abilities and intelligence. With Kumon learning methods many students can learn at up-class level, low-class level, and equivalent class level. Determining the level of Kumon is usually seen in students when attending Kumon classes for approximately six months to one year. However, by looking at several aspects that affect the level of students such as learning motivation, learning interests, learning habits, and gender of students, the Naive Bayes Classifier approach will be easy and fast in predicting kumon level for students. From the research using confussion matrix test, the result show the accuracy value of 70%, class precision of 75% for up-class level, class precision of 100% for low-class level, class precision of 60% for the equivalent of class level, class recall of 100% for up-class level, class recall of 25% low-class level, and class recall of 100% equivalent to class level. As a result, it is possible to conclude that the Naïve Bayes Classifier Algorithm can be used to predict the classification of kumon levels. However, it is hoped that the next research will use other attributes in order to get a more accurate algorithm.
Co-Authors Aden Aden Nina Valentika