AHP-Based Expert System for Identifying and Classifying Children’s Learning Difficulties
DOI:
https://doi.org/10.22303/csrid-.17.3.2025.311-325Keywords:
Sistem Pakar, Kesulitan Belajar, AHP, Diagnosis, Pendidikan, Teknologi InformasiAbstract
The rapid development of information technology has significantly impacted various sectors, including education. One of the common problems encountered in the educational field is learning difficulties in children, which may arise from internal or external factors such as poor concentration, limited reading ability, writing difficulties, or challenges in arithmetic skills. Undetected learning difficulties can hinder a child’s potential development and reduce learning motivation. Therefore, an intelligent system is needed to assist counseling teachers and parents in conducting early and objective identification. This study aims to design and implement an Expert System for Identifying Children’s Learning Difficulties using the Analytic Hierarchy Process (AHP) method. The AHP method was chosen due to its ability to assign priority weights to criteria and alternatives based on their level of importance. The study utilizes four main criteria: concentration (30%), reading ability (40%), writing ability (20%), and numerical ability (10%). The system was developed using a research and development (R&D) approach consisting of stages of requirement analysis, system design, implementation, and testing. The results indicate that the developed expert system can provide accurate and consistent identification results compared to manual AHP calculations. System validation tests achieved an accuracy rate of 99%, demonstrating high reliability in the decision-making process. Furthermore, the system has proven effective in assisting teachers and parents in detecting potential learning difficulties at an early stage, enabling faster and more precise interventions.
References
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: APA. https://doi.org/10.1176/appi.books.9780890425596
Prayitno, & Amti, E. (2014). Bimbingan dan konseling di sekolah dasar. Jakarta: PT Rineka Cipta.
Yusuf, M. H. (2016). Integrasi teknologi informasi dalam pembelajaran. Bandung: Alfabeta.
Turban, E., Aronson, J. E., Liang, T. P., & Sharda, R. (2011). Decision support systems and intelligent systems. Pearson Education.
Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.
Kusrini, & Istiyanto, J. (2007). Decision support system dengan metode AHP. Yogyakarta: Andi Offset.
UNESCO. (2020). Inclusive education. Paris: UNESCO. Retrieved April 5, 2025, from https://en.unesco.org/themes/leading-education/inclusive-education
OECD. (2022). Students with disabilities, difficulties and disadvantages. OECD Publishing. Retrieved April 5, 2025, from https://www.oecd.org/education/students-with-disabilities-difficulties-and-disadvantages/
Susilo, A. P., & Admodisastro, N. (2019). Penggunaan sistem pakar untuk identifikasi gangguan belajar anak berkebutuhan khusus. Jurnal Teknologi Informasi dan Pendidikan, 12(2), 45–52.
Putra, R. D., & Wijaya, A. (2020). Implementasi metode AHP dalam sistem pendukung keputusan untuk rekomendasi penanganan awal kesulitan belajar. Jurnal Ilmu Komputer dan Sistem Informasi, 8(1), 112–120.
Hidayat, M., & Rachmawati, N. (2021). Sistem pakar berbasis web untuk deteksi kesulitan belajar siswa dengan metode forward chaining. Jurnal Informatika dan Komputer Indonesia, 6(3), 98–106.
Sari, D. N., & Nugroho, R. (2022). Penerapan metode Analytic Hierarchy Process (AHP) dalam pengambilan keputusan pendidikan inklusif di sekolah dasar. Jurnal Pendidikan Dasar Nusantara, 7(2), 211–220.
Arifin, Z., & Putri, M. R. (2023). Rancang bangun sistem pakar berbasis AHP untuk diagnosis gangguan belajar pada anak usia dini. Jurnal Sistem Informasi dan Teknologi, 9(1), 55–63. https://doi.org/10.31002/jsit.v9i1.412
Rahmawati, N., & Fauzan, A. (2023). Analisis faktor penyebab kesulitan belajar membaca menggunakan pendekatan sistem cerdas. Jurnal Psikologi dan Pendidikan, 18(4), 302–314.
Prasetyo, H., & Dewi, L. (2024). Expert system for early detection of learning difficulties using AHP and fuzzy logic. International Journal of Artificial Intelligence in Education, 15(2), 122–134. https://doi.org/10.1016/j.ijaiedu.2024.02.003
Handayani, R., & Tanjung, F. (2024). Integrating decision support systems in educational diagnosis using hybrid AHP model. Journal of Educational Technology and Data Science, 12(1), 44–56. https://doi.org/10.1080/jedts.2024.112345
Suryani, E., & Kurniawan, T. (2021). Pengembangan sistem pakar untuk deteksi kesulitan belajar berbasis kecerdasan buatan. Jurnal Teknologi dan Sistem Informasi, 7(2), 178–186.*
Widodo, A., & Lestari, R. (2022). Decision support system for diagnosing learning disorders using AHP-TOPSIS integration. Procedia Computer Science, 207, 511–520. https://doi.org/10.1016/j.procs.2022.09.058
Hamzah, F., & Nuraini, S. (2023). Penerapan AHP dalam sistem pendukung keputusan pendidikan berbasis web. Jurnal Ilmiah Teknologi Informasi dan Sains, 13(4), 245–256.*
Chandra, M., & Setyawan, Y. (2024). Artificial intelligence approach for children’s learning difficulties detection in inclusive education. Education and Information Technologies, 29(3), 5159–5175.* https://doi.org/10.1007/s10639-024-12109
Lee, H., & Park, J. (2025). Adaptive decision-making models for early detection of student learning problems using hybrid AHP frameworks. Computers & Education: Artificial Intelligence, 7(1), 100–118.* https://doi.org/10.1016/j.caeai.2025.100118
