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Disleksia adalah gangguan belajar neurodevelopmental yang secara signifikan memengaruhi keterampilan membaca dan menulis anak-anak meskipun kecerdasannya normal, dan keterlambatan identifikasi dapat menyebabkan konsekuensi akademis dan psikososial jangka panjang. Metode skrining disleksia yang ada saat ini sangat bergantung pada penilaian yang dilakukan oleh ahli, yang memakan waktu, subjektif, dan sulit untuk diterapkan secara luas di lingkungan non-klinis. Meskipun penelitian terbaru telah mengeksplorasi pendekatan kecerdasan buatan (AI) untuk deteksi disleksia, banyak di antaranya masih terbatas pada data modalitas tunggal, analisis offline, atau implementasi non-seluler, sehingga membatasi penerapan praktisnya untuk skrining dini. Penelitian ini bertujuan untuk mengembangkan aplikasi seluler berbasis AI untuk deteksi disleksia dini dengan memanfaatkan data teks dan ucapan berurutan melalui arsitektur Jaringan Saraf Rekuren (RNN), khususnya Gated Recurrent Unit (GRU). Metodologi Penelitian dan Pengembangan (R&D) diterapkan, yang mencakup analisis persyaratan, desain sistem, pelatihan model GRU, pengembangan aplikasi seluler dengan Flutter, serta integrasi sistem dengan backend RESTful dan basis data MySQL. Model GRU dilatih menggunakan teks bacaan yang telah diproses sebelumnya dan rekaman suara untuk menangkap pola temporal yang terkait dengan perilaku membaca yang berhubungan dengan disleksia. Hasil eksperimen menunjukkan bahwa model yang diusulkan mencapai kinerja klasifikasi yang andal dalam mengidentifikasi pola terkait disleksia, sementara aplikasi seluler berhasil menyajikan hasil skrining secara real-time dan menyimpan catatan penilaian longitudinal. Temuan ini menunjukkan bahwa integrasi model pembelajaran mendalam sekuensial yang ringan ke dalam platform seluler menawarkan solusi yang dapat diskalakan dan mudah diakses untuk skrining disleksia dini, sehingga mendukung penggunaan mandiri oleh orang tua dan pendidik di luar lingkungan klinis.
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Declarations reported in the published article
Author Contributions
Muhamad Fathur Rahman: Conceptualization, Methodology, Software, Data Curation, Investigation, Writing – Original Draft, Writing – Review & Editing. Resmi Darni: Supervision, Resources, Validation, Writing – Review & Editing. Dony Novaliendry: Validation, Writing – Review & Editing. Khairi Budayawan: Supervision, Validation, Writing – Review & Editing. All authors have read and approved the final version of this manuscript.
Acknowledgments
The authors would like to thank all individuals, institutions, and external collaborators who provided invaluable guidance, technical support, and insights throughout the completion of this research. Their expertise significantly contributed to the rigor, quality, and practical relevance of this study.
View statement in PDF · PDF page 15Ethics Approval
This study did not involve direct experimental interventions on human or animal subjects. The research focused on application development and system testing. Data were collected through interviews with relevant participants after obtaining informed consent from parents or teachers. All data were processed anonymously to ensure privacy and confidentiality, and the study was conducted in accordance with applicable ethical research standards.
View statement in PDF · PDF page 15Informed Consent
Informed consent was obtained verbally from all participants involved in this study. For participants who were minors, consent was obtained from their parents, teachers, and the school authorities. All data collected was anonymized to protect the privacy and confidentiality of the participants.
View statement in PDF · PDF page 16Funding
The authors declare that this research was conducted independently and did not receive any external funding or financial support. All stages of the study, including system design, development, testing, and manuscript preparation, were carried out without external grants or sponsorships.
View statement in PDF · PDF page 16Data Availability
The data supporting the findings of this study are not publicly available due to privacy and confidentiality concerns related to the participants. Summary data are included in the manuscript, and additional information may be provided by the corresponding author upon reasonable request under strict confidentiality conditions.
View statement in PDF · PDF page 16Competing Interests
The authors confirm that there are no conflicts of interest, financial or otherwise, that could have influenced the research or the outcomes reported in this study.
View statement in PDF · PDF page 16Generative AI Disclosure
During the preparation of this manuscript, the author used generative AI and AI-assisted tools, including ChatGPT and Grammarly, to support language editing and proofreading. All content generated or assisted by these tools was carefully reviewed, revised, and validated by the author to ensure accuracy, originality, and academic integrity. The author takes full responsibility for the content of the manuscript and confirms that the use of these tools did not affect the study's scientific validity.
View statement in PDF · PDF page 16Referensi
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Hak Cipta (c) 2026 Muhamad Fathur Rahman, Resmi Darni, Dony Novaliendry, Khairi Budayawan