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...
| Publicado en: | SHS Web of Conferences Vol. 149; pp. 1 - 8 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
EDP Sciences
11/18/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=160498881&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 160498881 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 24165182 FT5R jtl: SHS Web of Conferences issn: 24165182 maglogo: N pubinfo: dt: 11/18/2022 vid: 149 pid: 76090 pub: EDP Sciences artinfo: ui: 160498881 10.1051/shsconf/202214901031 ppf: 1 ppct: 7 formats: tig: atl: Naïve Bayes for Analysis of Student Learning Achievement. aug: au: Pandiangan, N. Lintang, M. Priyudahari, B.A. affil: Departement of Computer Education, Universitas Musamus, Merauke, Indonesia sug: keyword: Classification Information System Naïve Bayes Algorithm student achievement ab: 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%. pubtype: Conference Proceedings doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2022 holdings: @attributes: islocal: N |
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