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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Taufan Bagus Dwi Putra Aditama
Master Program of Computer Science, FMIPA UGM, Yogyakarta
Computer Science & IT Control & Systems Engineering

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Journal : IJCCS (Indonesian Journal of Computing and Cybernetics Systems)

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Determining Community Structure and Modularity in Social Network using Genetic Algorithm Taufan Bagus Dwi Putra Aditama; Azhari SN
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 3 (2020): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.57834

Abstract

 Research on determining community structure in complex networks has attracted a lot of attention in various applications, such as email networks and social networks. The popularity determines the structure of a community because it can analyze the structure.Meanwhile, to determine the structure of the community by maximizing the value of modularity is difficult. Therefore, a lot of research introduces new algorithms to solve problems in determining community structure and maximizing the value of modularity. Genetic Algorithm can provide effective solutions by combining exploration and exploitation.This study focuses on the Genetic Algorithm which added a cleanup feature in the process. The final results of this study are the results of a comparison of modularity values based on the determination of the community structure of the Genetic Algorithm, Girvan and Newman Algorithm, and the Louvain Algorithm. The best modularity values were obtained using the Genetic Algorithm which obtained 0.6833 results for Zachary's karate club dataset, 0.7446 for the Bottlenose dolphins dataset, 0.7242 for the American college football dataset, and 0.5892 for the Books about US politics dataset.
Co-Authors Azhari SN