Implementasi Data Mining dengan Menerapkan Algoritma K-Means Clustering untuk Memberikan Rekomendasi Jurusan Kuliah Bagi Mahasiswa Baru

Authors

  • Ita Arfyanti STMIK Widya Cipta Dharma, Samarinda
  • Tommy Bustomi Politeknik Negeri Samarinda, Samarinda
  • Ivan Haristyawan STMIK Widya Cipta Dharma, Samarinda

DOI:

https://doi.org/10.30865/mib.v8i2.7429

Keywords:

Data Mining, Clustering, Recommendation, Major, K-Means Algorithm

Abstract

At the tertiary level, a student studies in a field of expertise or major that suits his or her area of talent and interest. Choosing an inappropriate college major will have consequences for the future of the prospective new student. In choosing a major, a prospective new student should choose a major that suits his abilities, both academically and his talents. One way to overcome prospective students who are wrong in choosing this major is to use the K-Means Clustering method. The K-Means algorithm is part of clustering data mining which has the role of forming new groups based on cluster formation. The K-Means Clustering algorithm can solve the problem of recommending majors to prospective new students based on school grades. The results of applying the K-Means algorithm show that in Cluster 1 there are 6 prospective students, in Cluster 2 there are 11 prospective students and in Cluster 3 there are 3 prospective students.

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Published

2024-04-30

Issue

Vol. 8 No. 2 (2024): April 2024

Section

Articles

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