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PENENTUAN JURUSAN PADA SMKN 1 MUARO JAMBI DENGAN METODE K-MEANS CLUSTERING
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This research is motivated by the lack of structure in determining the majors of class X students at SMKN 1 Muaro Jambi, because in the current majors they still use the manual system, namely written exams, this makes it difficult for students to determine majors according to their abilities. The problem in this study is how to apply data mining with the K-Means method in the application of student majors at SMKN 1 Muaro Jambi. How to design an application program for determining student majors at SMKN 1 Muaro Jambi using the K-Means method. This study uses the K-Means Clustering method to obtain majors that will make it easier for teachers or schools to determine student majors. K-means Clustering non-hierarchical method is a simple and effective algorithm to find groupings in the data in the majors process that is used is grade data and student data in the 2022/2023 entry year. The conclusion of this research is to produce a majors determination system using the K-Means Clustering method according to the majors criteria. Generating student majors from calculations using the K-means Clustering method.
Universitas Nurdin Hamzah
Title: PENENTUAN JURUSAN PADA SMKN 1 MUARO JAMBI DENGAN METODE K-MEANS CLUSTERING
Description:
This research is motivated by the lack of structure in determining the majors of class X students at SMKN 1 Muaro Jambi, because in the current majors they still use the manual system, namely written exams, this makes it difficult for students to determine majors according to their abilities.
The problem in this study is how to apply data mining with the K-Means method in the application of student majors at SMKN 1 Muaro Jambi.
How to design an application program for determining student majors at SMKN 1 Muaro Jambi using the K-Means method.
This study uses the K-Means Clustering method to obtain majors that will make it easier for teachers or schools to determine student majors.
K-means Clustering non-hierarchical method is a simple and effective algorithm to find groupings in the data in the majors process that is used is grade data and student data in the 2022/2023 entry year.
The conclusion of this research is to produce a majors determination system using the K-Means Clustering method according to the majors criteria.
Generating student majors from calculations using the K-means Clustering method.
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