1. Repository Universitas Mulawarman
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  3. J - Computer Sciences and Information Technology
Please use this identifier to cite or link to this item: http://repository.unmul.ac.id/handle/123456789/3898
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dc.contributor.authorTahyudin, Imam-
dc.contributor.authorHaviluddin, Haviluddin-
dc.contributor.authorNambo, Hidetaka-
dc.date.accessioned2020-03-10T00:30:57Z-
dc.date.available2020-03-10T00:30:57Z-
dc.date.issued2019-11-08-
dc.identifier.issn2277-8616-
dc.identifier.urihttp://repository.unmul.ac.id/handle/123456789/3898-
dc.description.abstractSome of the solutions for solving numerical Association rule mining problem are by discretization and optimization methods. The popular algorithms of optimization are A priori algorithms, Genetic algorithms (GA) and Particle swarm optimization (PSO). This research has aim to study time complexity of those optimization algorithms. The results show that the time complexity of evolutionary algorithms such as GA and PSO are faster than the time complexity of A priori algorithms.en_US
dc.language.isoenen_US
dc.publisherIJSTen_US
dc.subjecttime complexity; numerical association rule mining; a priori; evolutionary algorithmen_US
dc.titleTime Complexity Of A Priori And Evolutionary Algorithm For Numerical Association Rule Mining Optimizationen_US
dc.typeArticleen_US
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