K-Means Algorithm Implementation for Clustering of Foreign Tourists Visiting

Gita Muditha Kario, Endang Amalia

Abstract


The tourism sector plays an active role in economic growth for a country. Indonesia, which is one of the ASEAN states, shows that the role of tourism is one of the important sectors in the economy in Indonesia. However, the influence of the tourism sector has not been satisfactory for the government. The role of foreign tourist visits affects the economy in Indonesia by increasing foreign exchange for the country. In 2018, foreign exchange from the tourism sector continued to increase by 15.4 percent on an annual basis. However, it is unfortunate that Indonesia is still relatively small compared to other countries in the number of foreign tourist visits. The purpose of this study is to analyze the application of data mining in classifying the number of foreign tourist visits by Indonesia in ASEAN. The grouping is done by applying the K-Means clustering algorithm method. The data are grouped into 3 clusters, namely the high visit cluster (C1), the medium visit cluster (C2), and the low visit cluster (C3). So that the results obtained from the assessment of foreign tourist visits in ASEAN, namely, C1 namely Malaysia, C2 namely Singapore and Indonesia, and C3 namely the Philippines, Thailand, Vietnam, Myanmar / Burma, Brunei Darussalam, Cambodia, and Laos. The results of this study can be seen that Indonesia is in the medium visit grouping (C2). With this data, it can be a reference for the government to improve the tourism sector in visiting foreign tourists in Indonesia.

Full Text:

PDF

References


A. M. M. P. Senja, "Alasan Utama Turis Asing Berwisata ke Indonesia," 26 March 2019. [Online]. Available: https://travel.kompas.com/read/2019/03/26/171100327/alasan-utama-turis-asing-berwisata-ke-indonesia.. [Accessed March 2021].

I. CNN, "Menghitung Kontribusi Sektor Pariwisata Bagi Ekonomi RI," 26 February 2020. [Online]. Available: https://www.cnnindonesia.com/ekonomi/20200226121314-532-478265/menghitung-kontribusi-sektor-pariwisata-bagi-ekonomi-ri. [Accessed March 2021].

Suyanto, Data Mining Untuk Klasifikasi dan Klasterisasi Data, Bandung: Penerbit Informatika, 2017, p. 10.

R. Purohit and D. Bhargava, "An Illustration to Secured Way of Data Mining Using Privacy Preserving Data Mining," Journal of Statistics and Management Systems, p. 637, 2017. doi:https://doi.org/10.1080/09720510.2017.1395183.

E. Sikumbang, "Implementasi Data Mining Untuk Memprediksi Masa Studi Mahasiswa Menggunakan Algoritma C4.5 (Studi Kasus: Universitas Dehasen Bengkulu)," Jurnal Teknik Komputer, p. 156, 2018.

E. Prasetyo, Data Mining: Mengolah Data Menjadi Informasi Menggunakan Matlab, Bandung: Andi Offset, 2014, p. 15.

S. Nagari and L. Inayati, "Implementation of Clustering Using K-Means Method to Determine Nutritional Status," Jurnal Biometrika dan Kependudukan, p. 63, 2020. doi:10.20473/jbk.v9i1.2020.

Asroni 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, p. 78, 2015.

W. Azis and D. Atmajaya, "WS Azis and D Atmajaya. Pengelompokan Minat Baca Mahasiswa Menggunakan Metode K-Means," ILKOM Jurnal Ilmiah, pp. 89-90, 2016.

S. Handoko, Fauziah and E. Handayani, "Implementasi Data Mining Untuk Menentukan Tingkat Penjualan Paket Data Telkomsel menggunakan Metode K-Means Clustering," Jurnal Ilmiah Teknologi dan Rekayasa, pp. 80-81, 2020. doi:https://doi.org/10.35760/tr.2020.v25i1.2677.

S. Haryati, A. Sudarsono and E. Suryana, "Implementasi Data Mining Untuk Memprediksi Masa Studi Mahasiswa Menggunakan Algoritma C4.5 (Studi Kasus: Universitas Dehasen Bengkulu)," Jurnal Media Infotama, p. 133, 2015.

B. Rahmat, A. Gafar, N. Fajriani, U. Ramdani, F. Uyun, P. Yuwanda and N. Ransi, "Implementasi K-Means Clustering Pada RapidMiner Untuk Analisis Daerah Rawan Kecelakaan," Seminar Nasional Riset Kuantitatif Terapan, p. 60, 2017.

C. Kothari, Garg and Gaurav, Research Methodology: Methods and Techniques [Fourth multi color edition], New Age International, 2019, pp. 1-11.

A. Windarto, "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., 2017. doi:10.29099/ijair.v1i2.17.

F. Sibuea and A. Sapta, "Pemetaan Siswa Berprestasi Menggunakan Metode K-Means Clustering," JURTEKSI (Jurnal Teknologi dan Sistem Informasi), p. 88, 2017.


Refbacks

  • There are currently no refbacks.


Abava  Absolutech Convergent 2020

ISSN: 2307-8162