A Mobile-Based Expert System for Glaucoma Diagnosis Using the Naive Bayes Algorithm
DOI:
https://doi.org/10.47709/brilliance.v5i2.6633Keywords:
Glaucoma, Naïve Bayes, mobile-based, expert systemAbstract
This study aims to develop a mobile-based expert system application for early diagnosis of glaucoma using the Naive Bayes algorithm. The application is designed to help users recognize early symptoms of glaucoma, provide preliminary information, and increase public awareness to reduce the risk of vision loss or blindness. The application was developed using the Dart programming language, the Flutter framework, and Firebase as the database platform. The research method employed is Research and Development (R&D), utilizing the 4D development model, which consists of four stages: Define, Design, Develop, and Dissemination. To evaluate the functionality and effectiveness of the application, both black-box testing and expert validation were conducted. The Naive Bayes algorithm implemented in the application demonstrated a high accuracy rate of 97.50%, indicating strong reliability in recognizing symptom patterns and producing appropriate diagnostic predictions based on user input. Furthermore, the System Usability Scale (SUS) was used to assess the application's usability, yielding a high average score of 97.5%, reflecting excellent ease of use and user satisfaction. In addition, content validation by subject matter experts resulted in an average feasibility score of 98.07%, indicating that the application is highly suitable for public use in supporting early screening and diagnosis of glaucoma.
References
Al-Hikmah, M., Taufik, R., & Hastiah. (2024). Analysis Of The Characteristics Of Glaucoma Sufferers At Makassar Eye Hospital In 2019-2021. Jurnal of Opthalmology 2024, 1(1).
Febrianto Grahadi, R., Insani, R., & Rahmy Lidiawaty, B. (2024). Implementasi Metode Naive Bayes pada Sistem Diagnosis Penyakit Mata (Studi Kasus Poli Mata Rumah Sakit Islam Jemursari Surabaya). Fountain of Informatics Journal, 9(1), 25–29. https://doi.org/10.21111/fij.v9i1.11722
Halah, S. M., Hendracipta, N., & Nurhasanah, A. (2024). Pengembangan Video Pembelajaran pada Materi Ekosistem untuk Kelas V di SDN Jurumudi Baru. 12, 1093–1101.
Kurniawan, E., Nofriadi, & Nata, A. (2022). Penerapan System Usability Scale (Sus) Dalam Pengukuran Kebergunaan website Program Studi Di Stmik Royal. In Journal of Science and Social Research (Issue 1). http://jurnal.goretanpena.com/index.php/JSSR
Liu, H., Chen, C., Chen, Z., Li, Q., Li, Q., & Liu, W. (2023). Factors associated with delayed first ophthalmological consultation for primary glaucoma: a qualitative interview study. Frontiers in Medicine, 10, 1–11. https://doi.org/10.3389/fmed.2023.1161980
Martantoh, E., & Yanih, N. (2022). Implementasi Metode Naïve Bayes Untuk Klasifikasi Karakteristik Kepribadiaan Siswa Di Sekolah MTS Darussa’adah Menggunakan PHP MySQL. JTSI, 3(2), 166–175.
Maydiantoro, A. (2021). Model-model penelitian pengembangan (research and development). Jurnal pengembangan profesi pendidik indonesia (JPPPI).
Niati, E., & Sitohang, S. (2022). Sistem Pakar Diagnosa Penyakit Mata Glaukoma Dengan Metode Teorema Bayes. Jurnal COMASIE, 7, 117–124. http://ejournal.upbatam.ac.id/index.php/comasiejournal.
Rahman Burhani, H., & Fitri, I. (2021). Perbandingan Naïve bayes dan Certainty factor pada Sistem Pakar Untuk Mendiagnosa Dini Penyakit Glaukoma. Jurnal Teknologi Informasi Dan Komunikasi, 5(3), 291–299. https://doi.org/10.35870/jti
Riani Johan, J., Iriani, T., & Maulana, A. (2023). Penerapan Model Four-D dalam Pengembangan Media Video Keterampilan Mengajar Kelompok Kecil dan Perorangan. In Jurnal Pendidikan West Science (Vol. 01, Issue 06). Juni
Suardi. (2022). Rancang Bangun Sistem Pakar Diagnosis Penyakit Tanaman Padi dan Jagung Berbais Android.
Susilo, U. A., -, B. N. S., & -, A. R. (2025). Analisis Sentimen Opini Masyarakat Twitter Terhadap Kasus Diabetes Di Indonesia Menggunakan Algoritma Naïve Bayes Classifier. Jurnal Informatika Dan Teknik Elektro Terapan, 13(3). https://doi.org/10.23960/jitet.v13i3.6942
Yasir, F. N., Djusmin, V. B., & Ruhamah. (2023). Design and evaluation of mobile application interface for expert system of drug selection with local wisdom using Goal-Directed Design and heuristic evaluation approach. Brilliance: Research and Conceptual Journal, 3(2), 351–364. https://doi.org/10.47709/brilliance.v3i2.3335
WHO. (2023). Blindness and Vision Impairment.https://www.who.int/news-room/fact-sheets/detail/blindness-and-visual-impairment
Wiguna, I. K. A., Divayana, D. G. H., & Indrawan, G. (2025). Penentuan Faktor Pemicu Gejala Penyakit Mata Glaukoma, Astigmatis, Hipermetropi, dan Miopi. Journal of Applied Computer Science and Technology, 6(1), 29–36. https://doi.org/10.52158/jacost.v6i1.1113
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Amelia, Fajar Novriansyah Yasir, Sukmawati
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
info@itscience.org, web: 
