ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774


Applications of Partition-Based Algorithms for Clustering Dengue Patients in Sri Lanka


Abstract

Abstract Dengue is a mosquito-borne viral disease thathas rapidly spread in different regions of Asia, Latin America, Africa, andOceania over the past few years. Similarly, Sri Lanka is facing the sameepidemic challenges for more than two decades with the spread of the diseasevaries according to regions in a country. This paper aims to recognize thenumber of clusters among 26 regions in Sri Lanka that may explained somefactors that are contributing to the spread of the disease. The clustering wasperformed using partition-based clustering techniques namely k-means andk-medoids. The results show that the appropriate number of clusters of denguefever data is two, and one cluster consists of two regions, and other clustercontains the rest regions.  This studymay help the health sector to analyses and explore the key factors associatedwith the dengue fever regions

Keywords: Clustering, dengue, data mining,k-means algorithm, k-medoids algorithm.  


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Submit Article (Vol. 3 Issue 10) 

B
efore 10th Nov. 2018 

Issue Publication   On 10th Nov. 2018