Rekomendasi Wisata Umbul dengan K-Means Clustering

Authors

  • Fajar Pamungkas
  • Didik Nugroho
  • Yustina Retno Wahyu Utami STMIK Sinar Nusantara, Indonesia

DOI:

https://doi.org/10.30646/tikomsin.v8i2.478

Abstract

District Klaten has many springs that are used by people for many things; one of them used for tourist attractions is umbul tourism. It is difficult to use K-Means Clustering Method for determine umbul tourism according to classification and spread in district Klaten. K-Means Clustering is a method of grouping data by taking parameters of a number clusters, and partitioning data into clusters, based on similarities between data in one cluster and dissimilarities between different clusters, the center of the cluster is the average of the cluster member values it called as centroid. The results of this study are grouping the umbul truism which are divided into three clusters namely Enough, Good and The Best. The result of the data, there are 4 umbul tourisms in the first cluster is Beautiful category, namely Tirtomoyo, Buto, Pancuran, and Besuki. In the third cluster of umbul tourism has good category, namely Tirto Mulyani umbul, Gedaren, Sumber Nila, Manten, Sigedang, and Kajen. In the best category in the second cluster has 8 umbul tourisms, namely Nila umbul, Tirto Mulyono, Ingas, Lumban Tirto, Ponggok, Tirto Raharjo, Jolotundo, and Tirtomulyono.

Keywords: K-Means Clustering, Umbul, Umbul Category, Tourist Destination

References

H. Kamber, "Data Mining Concepts and Techniques." Canada: morgan kaufmann, 2011.

Hartatik, “Pengelompokan Mahasiswa Berdasarkan Nilai Ujian Nasional Dan Ipk Menggunakan Metode K-Means,†Pros. Semin. Nas. Inform., pp. 35–40, 2014.

F. Nasari and S. Darma, Penerapan K-Means Clustering Pada Data Penerimaan Mahasiswa Baru (Studi Kasus : Universitas Potensi Utama), Seminar Nasional Teknologi Informasi dan Multimedia, pp. 6–8, 2015.

F. A. Syam, “Implementasi Metode Klastering K-Means Untuk Mengelompokan Hasil Evaluasi Mahasiswa,†Ilmu Komput. dan Bisnis, vol. 8, no. Sunjana 2010, pp. 1841–1846, 2017.

P. Eko, DATA MINING - Konsep dan Aplikasi Menggunakan MATLAB. yogyakarta: penerbit andi, 2012.

N. Rohmawati, S. Defiyanti, and M. Jajuli, “Implementasi Algoritma K-Means Dalam Pengklasteran Mahasiswa Pelamar Beasiswa,†J. Ilm. Teknol. Inf. Terap., vol. I, no. 2, pp. 62–68, 2015.

R.S. Pressman, Rekayasa Perangkat Lunak (Pendekatan Praktisi) Edisi 7 Buku 1. Yogyakarta: penerbit andi, 2012.

Downloads

Published

2020-10-20

Issue

Vol. 8 No. 2 (2020): Jurnal TIKomSiN, Vol.8, No. 2, 2020

Section

Articles

Citation Check

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).

 

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.