Clustering Profil Pengunjung Perpustakaan Menggunakan Algoritma K-Means
(Studi Kasus Perpustakaan BP Batam)
Business Entity library Batam (BP Batam) is a public library located in Batam city with thw number of visitors. Every visitor who comes to do the charging guest book manually by writing system. It causes a buildup of data which are not organized. Data mining is one of the analytical tools that can be used to address the backlog of data. The method of Clustering with the K-Means Algorithm used in analyzing the data library visitors BP Batam. Library visitors using the data processing method of Elbow to get the best number of clusters K i.e., K = 3, and by using the center point (centroid) initial i,e, P1 = (4,1), P2 = (2,4), P3 = (4,2). The purpose of this research is to apply the algorithm for K-Means clustering in the data library visitors (case study library BP Batam). K-Means clustering results obtained from 1556 dataset data library visitors are grouped into three clusters, Clusters 1 is dominated by a college student and visitor located at Batam Center, Cluster 2 is dominated by a college student and visitor located at Bengkong, Cluster 3 is dominated by public and visitor status in Batam Center.
Agusta, Y., 2007, K-means - Penerapan, Permasalahan dan Metode Terkait, Jurnal Sistem dan Informatika Vol. 3 (Februari 2007): 47-60.
Bertalya., 2009, Data Mining & Knowledge Discovery in Database, Universitas Gunadarma.
Bholowalia, Purnima., Kumar, Arvind., 2014, EBK-Means: A Clustering Techiniques based on Elbow Method and K-Means in WSN, International Journal of Computer Application (0975-8887), IX(105), pp. 17-24.
Cios, Krzysztof J., Lukasz A. Kurgan., 2002, Trends in Data Mining and Knowledge Discovery.
Han, Jiawei., Kamber, Micheline., 2006, Data Mining: Concepts and Techniques, Morgan Kaufman: San Fransisco.
Hilda, Widyastuti., 2012, Modul Pembelajaran Data Mining, Perpustakaan Politeknik Negeri Batam, Batam.
Kodinariya, T, M., Makwana, P, R., 2013, Review on determining number of cluster in K-Means Clustering, International Journal of Advance Research in Computer Science and Management Studies, I(6), pp. 90-95.
Lasa HS., 2007, Manajemen Perpustakaan Sekolah, Yogyakarta: Pinus Book Publisher.
Madhulatha, T. S., 2012, An Overview On Clustering Methods, IOSR Journal of Engineering, II(4), pp.719-725.
Michael Berry., Gordon S. Linoff., 2004, Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, John Willey & Sons, Inc.
Muchlisin, R., 2012, Pengertian, Jenis dan Tujuan Perpustakaan.
Santoso, S., 2010, Statistik Multivariat, Jakarta: Elex Media Komputindo.
Supranto, J., 2004, Analisis Multivariat: Arti Dan Interpretasi, Jakarta: Rineka Cipta.
Sutarno NS., 2006, Perpustakaan dan Masyarakat, Jakarta: Sagung Seto.
Widya, S.A., Dedy, A., 2016, Pengelompokkan Minat Baca Mahasiswa menggunakan Metode K-Means, Teknik Informatika, Jurnal Ilmiah ILKOM Vol.8 No.2, Universitas Muslim Indonesia.
Yudho, GS., 2003, Penerapan Data Mining, Artikel Populer IlmuKomputer.com.
Copyright (c) 2017 Fauziah Mahmuda
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).