Data Mining Penentuan Jurusan Siswa Menggunakan Metode Agglomerative Hierarchical Clustering (AHC

Authors

  • Rima Tamara Aldisa Universitas Nasional, Jakarta

DOI:

https://doi.org/10.30865/mib.v7i2.6092

Keywords:

Data Mining, AHC Method, Student Majors

Abstract

There are various students who experience problems during the learning process because the chosen major does not match their abilities because choosing a major is only influenced by other people so that it is not in accordance with their abilities and a teacher is also difficult to adjust the abilities of one student to other students. In order for these students to be grouped with students who have the same level of knowledge, a grouping is carried out using data mining techniques in order to obtain new information in a database that has a large size or large amount of data to make it easier for users to obtain this information. The method used is AHC which is utilized as clustering with the single linkage method, the single link method is considered more effective than other methods because the problem is very suitable where the grouping process is carried out based on each criterion of the distance between all alternatives. The criteria used were three criteria (Science Score, IPS Score, TPA Score) with a total of 121 students. The application of the AHC method is carried out by utilizing rapidminer so that the results obtained are more efficient and effective. The results that can be used by the school are cluster 0 totaling 93 students, cluster 1 totaling 10 students, cluster 2 totaling 10 students and cluster 3 totaling 8 students.

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Published

2023-04-27

Issue

Vol. 7 No. 2 (2023): April 2023

Section

Articles

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