Article Sidebar

Download
PDF
Statistic
Read Counter : 451 Download : 454

Downloads

Download data is not yet available.

Main Article Content

Abstract

So far, the problem of gathering information at the Library and Archives Office of Magelang Regency is relatively low. To increase reading interest, policies are needed to determine reading interest. So the data used is book transaction data. This study aimed to classify people's reading interests according to the number of borrowed books at the Magelang Regency Library and Archives Service using the K-Means Clustering method and to find out which book categories are most in demand by the public at the Magelang Regency Library and Archives Service. One way to manage this data is to use data mining using the K-Means method. The results of this study are low reading interest, evidenced by using 2 clusters and the category of books that are most in-demand Literature with a high cluster strength value, namely with a Silhouette Coefficient value of 0.7354.

Keywords

Reading Interest Data Mining K-Means Clustering

Article Details

References

  1. Aronson, J. E., Liang, T.-P., & MacCarthy, R. v. (2005). Decision support systems and intelligent systems (Vol. 4). Pearson Prentice-Hall Upper Saddle River, NJ, USA:
  2. Atmaja, E. H. S. (2019). Implementation of k-Medoids Clustering Algorithm to Cluster Crime Patterns in Yogyakarta. International Journal of Applied Sciences and Smart Technologies, 1(1). https://doi.org/10.24071/ijasst.v1i1.1859
  3. Azis, W. S., & Atmajaya, D. (2016). Pengelompokan Minat Baca Mahasiswa menggunakan Metode K-Means. ILKOM Jurnal Ilmiah, 8(2). https://doi.org/10.33096/ilkom.v8i2.51.89-94
  4. Bakker, E. (2020). Implementasi Data Mining Clustering Data Perpustakaan Menggunakan Algoritma K-Means untuk Menentukan Penambahan Koleksi Buku di Perpustakaan UPY. SEMINAR NASIONAL Dinamika Informatika.
  5. Manulang, D., Abdillah, L. A., & Kurniawan, K. (2017). Sistem Informasi Penjualan Online (E-Commerce) Menggunakan CMS Wordpress pada Toko Soraya Shop dengan Menerapkan Metode RAD. Seminar Hasil Penelitian Sistem Informasi Dan Teknik Inormatika Ke-3 (SHaP-SITI2017).
  6. Windarto, A. P. (2017). Implementation of Data Mining on Rice Imports by Major Country of Origin Using Algorithm Using K-Means Clustering Method. International Journal of Artificial Intelligence Research, 1(2). https://doi.org/10.29099/ijair.v1i2.17
  7. Yuda Irawan. (2019). Implementation Of Data Mining For Determining Majors Using K-Means Algorithm In Students Of SMA Negeri 1 Pangkalan Kerinci. Journal of Applied Engineering and Technological Science (JAETS), 1(1). https://doi.org/10.37385/jaets.v1i1.18