Naïve Bayes for Analysis of Student Learning Achievement.

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...

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Detalles Bibliográficos
Publicado en:SHS Web of Conferences Vol. 149; pp. 1 - 8
Autores principales: Pandiangan, N., Lintang, M., Priyudahari, B.A.
Formato: Artículo
Publicado: EDP Sciences 11/18/2022
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario: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%.