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dc.contributor.advisorSihombing, Poltak
dc.contributor.advisorNababan, Erna Budhiarti
dc.contributor.authorLubis, Muhammad Ridwan
dc.date.accessioned2023-01-24T05:13:11Z
dc.date.available2023-01-24T05:13:11Z
dc.date.issued2016
dc.identifier.urihttps://repositori.usu.ac.id/handle/123456789/80884
dc.description.abstractHybrid is using two methods to a problem with the aim to improve their approach towards the specified target data. Hybrid PSO-ANN one optimal algorithm to solve such predictions in football matches. The process begins with determining the outcome of test dataset with the neural network architecture, specify the input parameters, the value of weight up to the value of hidden layer and output layer. Then the optimization of the results of the first test on a training dataset optimized by Particle Swarm Optimization. Testing will continue over using back propagation neural network until the maximum iteration and the results of the initial approach the target value. Furthermore, from the output obtained to search the value of the average error.en_US
dc.language.isoiden_US
dc.publisherUniversitas Sumatera Utaraen_US
dc.subjectArtificial Neural Networken_US
dc.subjectParticle Swarm Optimizationen_US
dc.subjectFootball Predictionen_US
dc.titleMetode Hybrid Particle Swarm Optimization - Jaringan Saraf Tiruan Untuk Peningkatan Akurasi Prediksi Hasil Pertandingan Sepakbolaen_US
dc.typeThesisen_US
dc.identifier.nimNIM147038040
dc.identifier.nidnNIDN0017036205
dc.identifier.nidnNIDN0026106209
dc.identifier.kodeprodiKODEPRODI55101#TeknikInformatika
dc.description.pages68 Halamanen_US
dc.description.typeTesis Magisteren_US


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