High School Major Classification towards University Students Variable of Score Using Na ve Bayes Algorithm

Completeness of data in each institution, such as major in a university, is necessary. Data of former school has important role in the need of students data. However, there is no relationship between data of former school and variable of students score. The suitable classification used in this resea...

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Bibliographic Details
Published inScientific journal of informatics (Semarang) Vol. 4; no. 2; pp. 191 - 198
Main Authors Sudibyo, Usman, Astuti, Yani Parti, Kurniawan, Achmad Wahid
Format Journal Article
LanguageEnglish
Published 10.11.2017
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ISSN2407-7658
2460-0040
2460-0040
DOI10.15294/sji.v4i2.12017

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Summary:Completeness of data in each institution, such as major in a university, is necessary. Data of former school has important role in the need of students data. However, there is no relationship between data of former school and variable of students score. The suitable classification used in this research is data mining technique which is nave bayes algorithm. This algorithm is able to manage massive data with a relative fast timing. By using this algorithm, the data results 64.77% performances in classifying former major in school towards variable of score. Hence, the researchers optimize selection feature by using Backward Elimination and result 71.71% performances data. It concludes that performance increases with selection feature. The increasing shows that not all variable of score affects the former school major.
ISSN:2407-7658
2460-0040
2460-0040
DOI:10.15294/sji.v4i2.12017