Deteksi Tingkat Keparahan Autism Spectrum Disorder Pada Anak Dengan Fuzzy Decision Support System

Amanda, Patricia (2022) Deteksi Tingkat Keparahan Autism Spectrum Disorder Pada Anak Dengan Fuzzy Decision Support System. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Autism Spectrum Disorder (ASD) atau yang dikenal dengan gangguan spektrum autisme merupakan merupakan suatu gangguan perkembangan yang ditandai dengan adanya kekurangan pada aspek komunikasi dan interaksi sosial, kesulitan dalam melakukan komunikasi verbal dan non verbal, tingkah laku terbatas dan berulang, serta berbagai gejala lainnya. Gangguan autisme biasanya tampak pada anak sebelum usia 3 tahun hingga 7 tahun. Namun, banyak orang tua yang baru menyadari gejala autisme saat anak berusia di atas 10 tahun. Keterlambatan deteksi autisme menyebabkan ketidaktepatan penanganan dan memicu peningkatan jumlah penderita autisme. Pada penelitian ini, dirancang sebuah sistem deteksi berbasis fuzzy logic decision support yang bertujuan untuk mendeteksi tingkat keparahan ASD pada anak. Proses deteksi dilakukan dengan mengajukan pertanyaan seputar keadaan anak kepada orang tua sebagai acuan deteksi yang diambil dari modul deteksi ASD. Sistem ini juga dilengkapi dengan instrumentasi berupa wearable wireless sensors berupa akselerometer dan giroskop yang berfungsi untuk membaca sinyal gerakan flapping hand pada anak sebagai salah satu indikasi adanya repetitive behaviours yang diderita oleh anak ASD. Penelitian ini diharapkan dapat membentuk suatu sistem deteksi untuk mengetahui tingkat keparahan ASD yang diderita anak sedini mungkin. Hasil menunjukkan bahwa form assessment yang digunakan yakni M-CHART-R terbukti cukup akurat dalam pendeteksian kondisi awal subjek serta sensor deteksi flapping hand yang digunakan mampu mendeteksi flapping hand yang muncul pada subjek dengan RMSE sebesar 0,356133 untuk modul sensor 1 dan sebesar 0,30866 untuk modul sensor 2. Saran pengembangan lebih lanjut adalah sistem hardware dan software dapat dijadikan embedded system sehingga seluruh sistem dapat bekerja secara real time serta proses pengolahan data secara keseluruhan dilakukan di mikrokontroler menggunakan bantuan database IoT, tanpa bantuan bluetooth.
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Autism Spectrum Disorder (ASD) is a developmental disorder characterized by lack of communication and social interaction, difficulty in verbal and non-verbal communication, limited and repeated behavior, and other symptoms. Autism disorders typically occur in children before the age of 3 years to 7. However, many new parents are aware of the symptoms of autism when children are over the age of 10. Late detection of autism leads to inaccuracies and leads to an increase in the number of people with autism. In this study, a fuzzy logic decision support based detection system aimed at detecting ASD severity in children was designed. The detection process is carried out by asking parents questions about the child's state as a detection reference taken from the ASD detection module. The system is also equipped with wearable wireless sensors in the form of accelerometers and gyroscopes to read the child's flapping hand motion signals as an indication of the repeat behavior of ASD children. This study is expected to establish a detection system to determine the severity of ASD in children as early as possible. The results show that the M-CHART-R formulation has proven quite accurate in detecting the subject's initial condition as well as the hand flapping detection sensor used to detect flapping hand appearing in subjects with an RMSE of 0.356133 for sensor module 1 and 0.30866 for sensor module 2. Further development suggestions are that the hardware and software systems can be embedded systems so that the entire system can work in real time and the overall data processing is done on the microcontroller using the help of an IoT database, without the help of Bluetooth.

Item Type:	Thesis (Other)
Additional Information:	RSB 621.381 536 Ama d-1 2022
Uncontrolled Keywords:	Autism Spectrum Disorder (ASD), Repetitive Behaviours, Flapping hand, Fuzzy Logic, Wearable Sensors. Autism Spectrum Disorder (ASD), Repetitive Behaviours, Flapping hand, Fuzzy Logic, Wearable Wireless Sensors
Subjects:	R Medicine > R Medicine (General) > R857.M3 Biomedical materials. Biomedical materials--Testing.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Biomedical Engineering > 11410-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	18 Jun 2026 06:11
Last Modified:	18 Jun 2026 06:11
URI:	http://repository.its.ac.id/id/eprint/133891

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