Surabaya Tourism Destination Recommendation Using Fuzzy C-Means Algorithm

Raymond Sutjiadi, Edwin Meinardi Trianto, Adriel Giovani Budihardjo

Abstract


Determining tourism destination requires various criteria that suitable for the travelers’ needs. Usually, travelers explore tourism destination through the internet or have recommendation from their relatives. That way is not informative because most people will recommend well-known tourism destination based on their experience only. In this research, C-Means Fuzzy Clustering is used to build a decision support system in selecting tourism destination in Surabaya, Indonesia. By using this application, the travelers, who want to visit Surabaya city, is not only provided the information related to tourism destination, but also nearest hotel and restaurant that suitable to traveler’s criteria and budget. This application processes the input into the desired output in the form of recommendation based on the calculation of the degree of membership and center of the cluster.

Keywords


Clustering; Fuzzy C-Means; Recommendation System; Tourism Destination;

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References


H. Santosa, “Environmental Management in Surabaya with Reference to National Agenda 21 and the Social Safety Net Programme,” Environment & Urbanization, Vol. 12, No. 2, pp. 175-184, October 2000

H. Ming-Chuan and Y. Don-Lin, “An Efficient Fuzzy C-Means Clustering Algorithm,” in Proceedings 2001 IEEE International Conference on Data Mining, pp. 225 – 232.

A.K. Jain, M.N. Murty, and P.J. Flynn, “Data Clustering: A Review,” ACM Computing Surveys, Vol. 31, No. 3, pp. 264-323, September 1999.

R.Suganya and R.Shanthi, “Fuzzy C-Means Algorithm-A Review,” International Journal of Scientific and Research Publications, Vol. 2, Issue 11, November 2012.

J. Chen, D. Pi, and Z. Liu, “An Insensitivity Fuzzy C-means Clustering Algorithm Based on Penalty Factor,” Academy Publisher, pp. 2379- 2384, 2013.

F. Klawonn, “Fuzzy Clustering: Insights and a New Approach,” Mathware & Soft Computing, Vol. 11, pp. 125-142, 2004

Z. Cebeci and F. Yildiz, “Comparison of K-Means and Fuzzy C-Means Algorithms on Different Cluster Structures,” Journal of Agricultural Informatics, Vol. 6, No. 3, pp. 13-23, October 2015.


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ISSN: 2180-1843

eISSN: 2289-8131