Sistem Monitoring Terintegrasi untuk Pencatatan dan Evaluasi Harian Kesehatan Anak dengan Autism Spectrum Disorder

Julina, Rifha Najwa (2026) Sistem Monitoring Terintegrasi untuk Pencatatan dan Evaluasi Harian Kesehatan Anak dengan Autism Spectrum Disorder. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Autism Spectrum Disorder (ASD) merupakan gangguan neurodevelopmental yang memerlukan pemantauan kondisi harian secara konsisten untuk mendukung proses intervensi dan evaluasi perkembangan anak. Namun, pencatatan kondisi harian yang dilakukan oleh caregiver, seperti orang tua dan guru, masih sering belum terstruktur, sulit diakses dan belum dipantau secara terintegrasi oleh tenaga kesehatan. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem monitoring terintegrasi berbasis mobile health (mHealth) yang berfungsi sebagai Personal Health Record (PHR) untuk mendukung pencatatan, pemantauan, dan evaluasi kondisi harian anak dengan ASD. Sistem dikembangkan menggunakan separated backend architecture, dengan framework Laravel sebagai layanan utama untuk manajemen data, autentikasi, dan otorisasi pengguna, serta framework Flask sebagai layanan komputasi untuk proses fuzzy inference. Mekanisme keamanan sistem menerapkan autentikasi berbasis Bearer Token dan Role-Based Access Control (RBAC) untuk membatasi hak akses pengguna sesuai peran masing-masing, yaitu orang tua, guru, dan tenaga kesehatan profesional. Pertukaran data antar layanan dilakukan melalui RESTful Application Programming Interface (REST API) untuk mendukung interoperabilitas dan skalabilitas sistem. Analisis kondisi anak dilakukan menggunakan metode Hierarchical Fuzzy Inference System (FIS) Mamdani yang mengolah sembilan parameter masukan yang merepresentasikan aspek emosional, kondisi fisik, dan pola aktivitas harian anak. Proses inferensi menghasilkan klasifikasi kondisi anak ke dalam tiga kategori, yaitu Normal, Need Attention, dan Critical, yang selanjutnya digunakan sebagai dasar pemberian umpan balik kepada caregiver. Pengujian fungsional dilakukan terhadap seluruh endpoint REST API, mekanisme autentikasi, serta implementasi RBAC. Hasil pengujian menunjukkan bahwa sistem mampu menjalankan proses pertukaran data, validasi akses pengguna, dan integrasi layanan backend secara optimal sesuai dengan rancangan sistem. Selain itu, pengujian usability menggunakan metode System Usability Scale (SUS) menghasilkan skor rata-rata sebesar 68.75, yang termasuk dalam kategori Marginal Acceptable, dengan Grade C dan Adjective Rating OK. Berdasarkan hasil implementasi dan pengujian yang dilakukan, dapat disimpulkan bahwa sistem monitoring terintegrasi yang dikembangkan mampu mendukung pencatatan dan pemantauan kondisi harian anak ASD secara lebih terstruktur, objektif, dan aman. Sistem juga menunjukkan tingkat penerimaan pengguna yang baik sehingga berpotensi menjadi sarana pendukung bagi caregiver dan tenaga kesehatan dalam proses pemantauan perkembangan anak secara berkelanjutan.
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Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that requires continuous daily monitoring to support intervention programs and evaluate children developmental progress. However, daily records maintained by caregivers, such as parents and teachers, are often subjective, unstructured, and difficult for healthcare professionals to access and monitor in an integrated manner. This study aims to design and implement an integrated mobile health (mHealth) monitoring system functioning as a Personal Health Record (PHR) to facilitate recording, monitoring, and evaluation of the daily condition of children with ASD. The system was developed using separated backend architecture, where Laravel serves as the primary service for data management, user authentication, and authorization, while Flask is utilized as an intelligent computation service for fuzzy inference processing. System security is implemented through Bearer Token-based authentication and Role-Based Access Control (RBAC), ensuring that access permissions are restricted according to user roles, namely parents, teachers, and healthcare professionals. Data exchange between services is conducted through a RESTful Application Programming Interface (REST API), enabling system interoperability and scalability. The child condition is assessed using a Hierarchical Mamdani Fuzzy Inference System (FIS), which processes nine input parameters representing emotional conditions, physical health status, and daily activity patterns. The inference process generates one of three condition classifications: Normal, Need Attention, or Critical. These classifications are then utilized to provide adaptive feedback to caregivers. Functional testing was conducted on all REST API endpoints, authentication mechanisms, and RBAC implementations. The results demonstrate that the system successfully performs data exchange, user access validation, and backend service integration in accordance with the proposed system design. Furthermore, usability evaluation using the System Usability Scale (SUS) yielded an average score of 68.75, which falls within the Marginal Acceptable category, corresponding to Grade C and an “OK” adjective rating. Based on the implementation and evaluation results, it can be concluded that the proposed integrated monitoring system can support structured, objective, and secure daily monitoring of children with ASD. The system also demonstrates satisfactory user acceptance, indicating its potential as a supportive tool for caregivers and healthcare professionals in monitoring children developmental conditions continuously.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Autism Spectrum Disorder, Mobile Health, Personal Health Record, Hierarchical Fuzzy Inference System, Role-Based Access Control
Subjects:	R Medicine > RJ Pediatrics > RJ101 Child Health. Child health services T Technology > T Technology (General) > T57.5 Data Processing T Technology > T Technology (General) > T58.6 Management information systems T Technology > T Technology (General) > T58.62 Decision support systems T Technology > T Technology (General) > T58.64 Information resources management T Technology > T Technology (General) > T59.7 Human-machine systems.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Biomedical Engineering > 11410-(S1) Undergraduate Thesis
Depositing User:	Rifha Najwa Julina
Date Deposited:	01 Aug 2026 07:11
Last Modified:	01 Aug 2026 07:11
URI:	http://repository.its.ac.id/id/eprint/138165

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