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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Mantik Penusa Simtek : Jurnal Sistem Informasi dan Teknik Komputer Building of Informatics, Technology and Science U-NET Jurnal Teknik Informatika J-COSCIS : Journal of Computer Science Community Service CSRID
Subagio, Selamat
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science Social Sciences

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AHP-Based Expert System untuk Mengidentifikasi dan Mengklasifikasikan Kesulitan Belajar Anak Samsir, Samsir; Sahmuda, Arjana; Subagio, Selamat
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 3 (2025): Oktober 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.3.2025.311-325

Abstract

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.
Co-Authors Ainun, Annisa Azhar, Wahyu Dalimunthe, Abdul Hakim Harahap, Fauji Has, Syahnila Natasya Khoirul Anwar Misman Panjaitan, Indra Syahputra Rahmad Aditiya Rahmayani Rahmayani Rambe, Shopiah Anggraini Ritonga, Sahbuki Ronal Watrianthos Sahmuda, Arjana Samsir Samsir Samsir Samsir Samsir, Samsir Sangkot Idris Ritonga Saragih, Reagan Surbakti Siagian, Taufiqqurrahman Nur