Implementasi Metode Fuzzy K-Nearest Neighbor Pada Klasifikasi Gangguan Autisme Anak
Total View This Week0

Institusion

Institut Teknologi Perusahaan Listrik Negara

Author

Rizaldi, Tri Shangrilla
Kuswardani, Dwina
Affandi, Riki Ruli

Subject

Teknik Informatika 

Datestamp

2023-06-20 06:59:24 

Abstract :
This study aims to implement the Fuzzy K-Nearest Neighbor method in the classification of children's autism disorders so that the classification can make it easier to use it in the clinical team to classify children including autism or non-autism. Autism is a developmental disorder in children experiencing delays in the functions of cognitive, language, behavior and social interactions. Increased prevalence of autism children due to lack of understanding of the symptoms that appear in the development of their growth and development. So that the classification method is carried out as a result of decisions for children on the symptoms that arise. The method used with Fuzzy K-Nearest Neighbor because this method provides a value for the degree of membership in the test data class so that the results obtained are not ambiguous. From the results of research conducted testing that the highest accuracy value in the use of the amount of K = 5 with an accuracy of 89.7% 

File :
201731221_TriShangrillaRizaldi_SKRIPSI.pdf