Penerapan Algoritma Decision Tree Untuk Menentukan Terapi Pada Anak Autis
DOI:
https://doi.org/10.29408/jit.v8i1.26121Keywords:
Autisme, Classification, Decision Tree, Psychomotor TherapyAbstract
People with hearing and speech impairments often have difficulty communicating with the general public due to a This research focuses on the development of a classification system for autism levels in children using the Decision Tree algorithm. This system considers various aspects of the psychomotor abilities of autistic children, such as balance, hand coordination, flexibility, and muscle strength. Observation data was taken from autistic children aged 5-8 years who attended SLB Anugerah Colomadu, and was used to build a Decision Tree model. The results showed that this model had 0,9 accuracy in classifying autism rates based on the observed psychomotor features. In addition to classification, the system also provides recommendations for psychomotor therapy that are specific and according to the level of autism that the model has classified. This approach is expected to improve the quality of interventions for autistic children by facilitating the development of their psychomotor skills. With this system, it is hoped that educators and therapists can provide more targeted treatment, so that autistic children can develop more optimally according to their individual needs. This structured and data-based approach is also expected to be a reference in the development of other intervention methods in the future
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