PENERAPAN TINGKAT MINAT BACA SISWA SD INPRES 037145 MENGGUNAKAN K-MEANS

Anita Anita (Universitas Prima Indonesia)
Herwin Simbolon (Universitas Prima Indonesia)

Rang Teknik Journal
Vol 4, No 2 (2021): Vol. 4 No. 2 Juni 2021

Grouping students' reading interest based on the criteria for books read, books borrowed, and also considering the number of books available can help in the process of adding to the existing book collection in the library. One way to manage this data is by using data mining by utilizing the K-Means method. Book data are grouped into 3 clusters, namely priority, consideration, and not prioritization in planning for additional book collections. The result of this research is that the cluster with the largest value in the final centroid is the recommended cluster in planning to add to the book collection.