Application of Expectation-Maximization (EM) Algorithm in Grouping Popularity Tourism Objects in Malang Raya Based on Indicator of Many Visitors
AbstractMalang Metropolitan Area is one of the areas in East Java which is a leading tourism destination in Indonesia with Batu Tourism City (Kota Wisata Batu) as the center. Considering the development of tourism in Malang, it is necessary to do a grouping of the popularity of tourism objects so that it can be used as a reference for making policy by the tourism department and tourism management. In this article, the grouping is analyzed by using the method of grouping the Expectation Maximation (EM) algorithm. The data used is secondary data obtained from BPS data, namely data of many tourism visitors in Malang Raya. The results of the grouping the popularity of leading tourism objects in Malang are based on indicators of the number of visitors divided into five groups, there are Group 1: Selecta; Group 2: Balekambang, Pemandian Wendit and Wisata Oleh-Oleh Brawijaya; Group3: Museum Angkut, Coban Rondo, Museum Satwa, Jatim Park, BNS, Petik Apel “Makmur Abadi and Agro Kebun Teh Wonosari; Group 4: Kusuma Agro Wisata, Kampoeng Kidz, Air Panas Cangar, Eco Green Park, Predator Fun Park, Wana Wisata Coban Rais, Gunung Banyak, Mahajaya T-Shirt & Oleh-oleh, Ngliyep and Bendungan Selorejo; Group 5: Vihara “Dammadhipa Arama”, Rafting “Kaliwatu”, Batu Rafting, Wana Wisata Coban Talun, Pemandian Tirta Nirwana, Pemandian Air Panas Alam Songgoriti, Wonderland Waterpark, Sahabat Air Rafting, Petik Apel Mandiri, Batu Agro Apel, Kampung Wisata.
E. Kurniawan, “Malang City Government Concentration on Boosting Tourism to Increase PAD”. 2017. https://malangtoday.net/malang-raya/kota-malang/dongkrak-pariwisata-untuk-tingkatkan-pad/amp/
R. Silvi, “Analisis Cluster dengan Data Outlier Menggunakan Centroid Linkage dan K-Means Clustering untuk Pengelompokkan Indikator HIV/AIDS di Indonesia”, mantik, vol. 4, no. 1, pp. 22-31, May 2018.
S. Borman, “The Expectation Maximization Algorithm: A Short Tutorial”, July 2006.
T. A. Kusuma and Suparman. “Algoritma Expectation-Maximization (EM) untuk Estimasi Distribusi Mixture”, Jurnal Konvergensi, Vol. 4, No. 2 Oktober 2014.
R. E. D. Sirait, E. Darwianto, and D. D. J. Suwawi, “Implementasi dan Analisis Algoritma Clustering Expectation–Maximization (EM) pada Data Tugas Akhir Universitas Telkom”, e-Proceeding of Enginering, Vol. 2, No. 2, Agustus 2015.
I. Johari, D. Soeyapto, and Mardiani, “Penerapan data Mining untuk Data Jumlah Kendaraan Menggunakan Algoritma Expectation Maximization (EM) pada Dispenda Kota Palembang”, STMIK MDP, 2015.
Clustering, K. “Implementation and Analysis of Clustering Expectation - maximization (EM) Algorithms on Telkom University Final Project Data”, Vol. 2, No. 2, pp. 6711–6717, 2015.
S, Santoso, “Statistik Multivariat: Konsep dan Aplikasi dengan SPSS”, Jakarta. Elex Media Komputindo, 2004.
A. C. Rencher, “Method of Multivariate Analysis (Second Edition)”, New York: John Wiley and Sons, Inc. 2002.
L. J. Bain and M. Engelhardt, “Introduction to Probablity and Mathematical Statistcs”. California: Duxbury Press. 1992.
Kusrini and E. T. Luthfi, “Algoritma Data Mining”, Yogyakarta: Andi, 2009.
H. Glanz, H and L. Carvalho, “An expectation-maximization algorithm for the matrix normal distribution with an application in remote sensing”. Journal of Multivariate Analysis, Vol. 167, pp. 31-48, September 2018, doi: 10.1016/j.jmva.2018.03.010.
G. J. McLachlan and T. Krishnan, “The EM Algorithm and Extensions”, John Wiley & Sons, Hoboken, 2008, doi: 10.1002/9780470191613.
Copyright (c) 2019 Nur Atikah
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons License that allows others to share the work with an acknowledgment 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 acknowledgment 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