Smart Diagnosis: Android Expert System for Detecting ADHD Behavior Types in Children

This study aims to develop an application capable of detecting ADHD behavioral disorders in children aged 3–8 years. This study employs a Research and Development (R&D) approach using forward chaining. The application was tested through functional testing using black-box testing, expert validation, and system effectiveness testing—the effectiveness testing aimed to evaluate the system's accuracy and user satisfaction. The results of this research indicate that the application functions as intended based on the functional testing. According to expert validation, the application accurately reflects the symptoms associated with ADHD behavior. In terms of effectiveness, the application demonstrated a reliable level of accuracy and was found to be user-friendly. This application helps accelerate the early identification process in children suspected of having ADHD behavior so that professionals can immediately follow it up.

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Publication Details

Journal
Jurnal Teknologi dan Manajemen Informatika
Published
2025-07-04
DOI
https://doi.org/10.26905/jtmi.v11i1.15498
Primary Topic
Varied Academic Research Topics
Type
article
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article

Smart Diagnosis: Android Expert System for Detecting ADHD Behavior Types in Children

Chaulina Alfianti Oktavia, Andrew Christianto, Syntia Widyayuningtias Putri Listio
Jurnal Teknologi dan Manajemen Informatika
Varied Academic Research Topics
article

Smart Diagnosis: Android Expert System for Detecting ADHD Behavior Types in Children

Chaulina Alfianti Oktavia, Andrew Christianto, Syntia Widyayuningtias Putri Listio
article en

Abstract

This study aims to develop an application capable of detecting ADHD behavioral disorders in children aged 3–8 years. This study employs a Research and Development (R&D) approach using forward chaining. The application was tested through functional testing using black-box testing, expert validation, and system effectiveness testing—the effectiveness testing aimed to evaluate the system's accuracy and user satisfaction. The results of this research indicate that the application functions as intended based on the functional testing. According to expert validation, the application accurately reflects the symptoms associated with ADHD behavior. In terms of effectiveness, the application demonstrated a reliable level of accuracy and was found to be user-friendly. This application helps accelerate the early identification process in children suspected of having ADHD behavior so that professionals can immediately follow it up.

Jurnal Teknologi dan Manajemen InformatikaVol. 11(1)
Universitas Dian Nusantara (ID)
Openalex Percentile: Top 65%
Varied Academic Research Topics
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