KLASIFIKASI GANGGUAN MOTORIK KASAR ANAK MENGGUNAKAN NAIVE BAYES SERTA OPTIMASI DENGAN PSO DAN ADABOOST

Abstract: Delayed in gross motor movements children is one of the children's growth disorders. Gross motor movements include large muscles such as muscular limbs in babies such as kicking, kicked, grabbed, lifted the neck, and turned. Growth in its ability to be monitored and stimulated so that children can grow and develop optimally. In this study aims to help classify the patients were categorized as patients with normal or impaired at the stage of the initial examination. By comparing algorithms Naïve Bayes classifier, Naive Bayes classifier with the optimization of PSO and Naive Bayes classifier based Adaboost in this study, the result of testing the accuracy value Naïve Bayes classifier amounted to 88.67%, while the Naive Bayes classifier based Adaboost amounted to 90.00% and the accuracy of the algorithm Naive Bayes classifier with PSO optimization of 98.00%.
Keywords: disorders of children, naïve bayes classifier, adaboost, PSO optimization
Penulis: Kadek Wibowo, Sfenrianto, Kaman Nainggolan
Kode Jurnal: jptkomputerdd150464

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