SHS Web Conf.
Volume 149, 2022International Conference on Social Science 2022 “Integrating Social Science Innovations on Post Pandemic Through Society 5.0” (ICSS 2022)
|Number of page(s)||7|
|Section||Education and Digital Learning|
|Published online||18 November 2022|
Naïve Bayes for Analysis of Student Learning Achievement
1 Departement of Computer Education, Universitas Musamus, Merauke, Indonesia
2 Departement of Computer Education, Universitas Musamus, Merauke, Indonesia
3 Departement of Computer Education, Universitas Musamus, Merauke, Indonesia
* Corresponding author: email@example.com
Student achievement is measured by the achievement index value obtained every semester,student achievement is measured by several factors, and in this research the author takes several factors including study paths, choice of majors, monthly living expenses, relationships with friends, relationships with family, motivation study, employment, scholarships, transportation, and internet services. Analysis and prediction of student achievement using Naïve Bayes Algorithm classification method, the result is this algorithm works very well using 14 student datasets to determine the grades of the 15th student. Based on theAnalysis, variables that affect student achievement include choice of majors, residence, relationships with friends, relationships with family, job, and scholarships. The accuracy of the naïve bayes algorithm for this student achievement case study model reaches 60%, precision 25%, and recall 100%.
Key words: Naïve Bayes Algorithm / Classification / Information System / student achievement
© The Authors, published by EDP Sciences, 2022
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