WEB USAGE MINING MENGGUNAKAN K-MEANS UNTUK MENGETAHUI KECENDERUNGAN AKSES PENGGUNA (STUDI KASUS: GANTO.CO)

Rizky Maulana(1), Nurindah Dwiyani(2),
(1)   Indonesia
(2) Universitas Negeri Padang  Indonesia

Corresponding Author


DOI : https://doi.org/10.24036/voteteknika.v6i2.102003

Full Text:    Language : id

Abstract


The Ganto website, ganto.co, is one source of information for students, lecturers, and the public. Every visit to the Ganto website is recorded on the server log. If left unchecked, the server log will only fulfill server storage. Therefore, actions need to be taken such as implementing Web usage mining. Web usage mining, using k-means clustering, is one way to ensure the satisfaction of users who access the Ganto website, by knowing the tendency of user access through server log analysis. First Cluster, September 2017. Second Cluster, October 2017, November 2017, December 2017, February 2018, March 2018, and April 2018. While the third cluster, July 2017, August 2017, January 2018, May 2018, and June 2018. Results of analysis , Berita is the most frequently viewed rubric, the second is Artikel, and the third is E-Paper. While the other rubrics (Info Kampus, Sastra Budaya, Ganto TV, and Ganto Foto) are not too often viewed by users or visitors of the Ganto website.

Keywords: Web usage mining, clustering, k-means, Ganto


References


I. T. Syamnugroho and R. Efendi, "Pengembangan Website SMK Negeri 4 Semarang," Jurnal Teknologi Informasi dan Komunikasi, vol. V, no. 2, Agustus 2014.

S. Hapsari, "Pembuatan Website pada Google Original Movie Rental Pacitan," Journal Speed: Sentra Penelitian Engineering dan Edukasi, vol. II, no. 2, pp. 48-54, 2010.

"Tentang Kami," [Online]. Available: http://www.ganto.co/profil/1/tentang-kami.html. [Accessed 7 May 2018].

J. Srivastava, R. Cooley, M. Deshpande and P.-N. Tan, "Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data," SIGKDD Explorations, vol. I, no. 2, pp. 12-23, Januari 2000.

D. T. Larose and C. D. Larose, Discovering Knowledge in Data: An Introduction to Data Mining, 2nd ed., New Jersey: John Wiley & Sons, Inc., 2014.

H. Hamimi, "Analisis Data Anggaran Pendapatan Belanja Daerah Menggunakan Clustering K-Means dan Forecasting (Studi Kasus pada DPKA Kota Padang)," Jurnal Vokasional Teknik Elektronika dan Informatika (VOTEKNIKA), vol. II, no. 1, 2014.

H. K. Saputra, "Analisis Data Mining Untuk Pemetaan Mahasiswa Yang Membutuhkan Bimbingan dan Konseling Menggunakan Algoritma Naïve Bayes Classifier," Jurnal Teknologi Informasi dan Pendidikan, vol. 11, no. 1, pp. 14-26, 2018.

J. Han, M. Kamber and J. Pei, Data Mining: Concepts and Techniques, 3rd ed., Massachusetts: Morgan Kaufmann, 2012.

J. O. Ong, "Implementasi Algoritma K-means Clustering untuk Menentukan Strategi Marketing President University," Jurnal Ilmiah Teknik Industri, vol. XII, no. 1, pp. 10-20, June 2013.

"RapidMiner Studio," [Online]. Available: http://www.rapidminer.com/products/studio/. [Accessed 9 August 2018].

I. Lunden, "German Predictive Analytics Startup Rapid-I Rebrands as RapidMiner, Takes $5M from Open Ocean, Earlybird to Tackle the U.S. Market," [Online]. Available: https://techcrunch.com/2013/11/04/german-predictive-analytics-startup-rapid-i-rebrands-as-rapidminer-takes-5m-from-open-ocean-earlybird-to-tackle-the-u-s-market/. [Accessed 12 August 2018].

G. Deutsch, "RapidMiner from Rapid-I at CeBIT 2010," [Online]. Available: http://www.data-mining-blog.com/cloud-mining/rapidminer-cebit-2010/. [Accessed 12 August 2018].

"Redaksi," [Online]. Available: http://www.ganto.co/profil/4/redaksi.html. [Accessed 7 May 2018].

"Interview with RapidMiner's Ingo Mierswa, Ralf Klinkenberg, part 1," [Online]. Available: https://kdnuggets.com/2010/02/f-interview-rapid-i-founders.html. [Accessed 12 August 2018].

A. and R. Adrian, "Penerapan Metode K-means untuk Clustering Mahasiswa berdasarkan Nilai Akademik dengan Weka Interface Studi Kasus pada Jurusan Teknik Informatika UMM Magelang," Jurnal Ilmiah Semesta Teknika, vol. XVIII, no. 1, pp. 76-82, Mei 2015.

T. Khotimah, "Pengelompokan Surat dalam Alquran Menggunakan Algoritma K-means," Jurnal SIMETRIS, vol. V, no. 1, pp. 83-88, April 2014.


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