Implementasi Algoritma Teorema Bayes Dengan Pemodelan UML Untuk Mendiagnosis Tingkatan Gangguan Autisme Di SLB Pelita Hati

Finanta Okmayura; Weni Oktavia  Agus; Melati Angguni; Reihan Hersi Saputro; Nouval Ditya Mufty

doi:10.37859/coscitech.v5i2.7507

Finanta Okmayura Universitas Muhammadiyah RIau
Weni Oktavia Agus
Melati Angguni
Reihan Hersi Saputro
Nouval Ditya Mufty

https://doi.org/10.37859/coscitech.v5i2.7507

Keywords: Teorema Bayes, UML design, Autisme

Abstract

Autism, as a complex developmental disorder in children with special needs, involves delays in aspects of cognition, emotion, behavior, and social interaction. This research proposes an innovation by applying UML modeling and Bayes Theorem Algorithm to detect the level of autism disorder in Sekolah Luar Biasa (SLB) Pelita Hati. The SLB environment, faced with limited human resources and an increasing number of students, is a major challenge. The developed expert system provides an efficient solution with quick recommendations, reduces the expert's workload, and increases the detection accuracy of autism disorders. The expert approach with Bayes' Theorem provides an accurate insight into the complexity of autism disorders. Bayes' theorem is used to calculate the probability of events based on relevant observations. The application of UML modeling in the design of the expert system proved successful, producing an effective solution to support the diagnosis and treatment of autism disorders in SLB Pelita Hati. The results showed an accuracy of 94%, signifying a heavy level of confidence, with therapy recommendations such as Physiotherapy Therapy, Speech Therapy, Remedial Therapy, Cognitive Therapy, and Game Therapy, Occupational Therapy, Sensory Integrity. This research makes an important contribution in addressing the challenges in autism diagnosis approaches in special education settings.

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