Evaluation of Implementation Context Based Clustering In Fuzzy Geographically Weighted Clustering-Particle Swarm Optimization Algorithm

This paper contains an evaluation of the implementation Context Based Clustering method into Fuzzy Geographically Weighted Clustering-Particle Swarm Optimization (FGWC-PSO) algorithm on 11 variable from data factors causing the spread of dengue in East Java. Integration of Particle Swarm Optimizatio...

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Bibliographic Details
Main Authors: Siti Nurmardia Abdussamad, Suci Astutik, Achmad Effendi
Format: Article
Language:English
Published: Departement of Electrical Engineering, Faculty of Engineering, Universitas Brawijaya 2020-04-01
Series:Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems)
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Online Access:https://jurnaleeccis.ub.ac.id/index.php/eeccis/article/view/609
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Summary:This paper contains an evaluation of the implementation Context Based Clustering method into Fuzzy Geographically Weighted Clustering-Particle Swarm Optimization (FGWC-PSO) algorithm on 11 variable from data factors causing the spread of dengue in East Java. Integration of Particle Swarm Optimization as a metaheuristic algorithm makes the computation run longer so, the solution in this paper is FGWC-PSO will be combined with context based clustering to produce a hybrid method (CFGWC-PSO) which can shorten the computational time of the clustering algorithm. Context based clustering in this paper will use 3 ways, namely by using random values, using Fuzzy C-Means (FCM), and using mean and standard deviations. CFGWC-PSO algorithm using number of clusters = 2 and CFGWC-PSO will be evaluated using IFV index, based on processing results found that the best clustering algorithm is CFGWC-PSO using FCM
ISSN:2460-8122