IMPLEMENTATION OF K-MEANS ALGORITHM AS A CLUSTERING METHOD FOR SELECTING ACHIEVEMENT STUDENTS BASED ON ACADEMIC GRADE

  • Indah Dwijayanthi Nirmala (1*) Universitas Bhayangkara Jakarta Raya
  • Prima Dina Atika (2) Universitas Bhayangkara

  • (*) Corresponding Author
Keywords: K-Mean Method, Clustering, Siswa Berprestasi

Abstract

Increased student success and low student failure rates are a reflection of good quality in the field of education. Awareness of the importance of education determines the quality in utilizing existing resources, including human resources, facilities and infrastructure as well as technological resources. The large number of students in school as well as the variety of different abilities and academic qualifications for each student, makes it difficult for the school to facilitate the search for outstanding student selection based on academic scores. Therefore it is necessary to do the data to be processed into information and knowledge as a grouping of outstanding students from assignment scores, test scores, and student practice scores as variables that will be supporting values in the selection of outstanding students. Data mining can be proposed as an approach that can be used to predict the selection of outstanding students. In this study, the application of the kmeans clustering algorithm is proposed to predict the selection of outstanding students based on academic scores.

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Published
2020-09-15
How to Cite
Nirmala, I., & Atika, P. (2020). IMPLEMENTATION OF K-MEANS ALGORITHM AS A CLUSTERING METHOD FOR SELECTING ACHIEVEMENT STUDENTS BASED ON ACADEMIC GRADE. Pilar Nusa Mandiri : Journal of Computing and Information System, 16(2), 199-204. https://doi.org/10.33480/pilar.v16i2.1575
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