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%.
Penulis: Kadek Wibowo,
Sfenrianto, Kaman Nainggolan
Kode Jurnal: jptkomputerdd150464