Published: 2025-08-01
Expert System for Student Talent and Interest Using Certainty Factor and Dempster-Shafer Methods
DOI: 10.35870/ijsecs.v5i2.5169
Teddy Setiady, Gentur Wahyu Nyipto Wibowo, R. Hadapiningradja Kusumodestoni
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Abstract
Elementary education systems in Jepara Subdistrict currently lack standardized frameworks for identifying student capabilities, leaving educators and parents without reliable tools to recognize individual talents and interests. We developed a hybrid expert system that combines Certainty Factor and Dempster-Shafer methodologies to establish quantitative assessment protocols for elementary student aptitude evaluation. Our research employed a quantitative descriptive approach, gathering data through structured behavioral observations, educator interviews, validated questionnaires, and academic documentation from multiple elementary schools across the district. The system processes student behavioral patterns using Certainty Factor methods for initial inference, then applies Dempster-Shafer algorithms to combine evidence sources while managing assessment uncertainty and subjective evaluation parameters. Preliminary testing reveals the system can generate percentage-based aptitude measurements across various domains, with interest category evaluations reaching 37% in targeted areas. We evaluated performance through accuracy validation, expert correlation analysis, precision-recall calculations, response time measurement, and knowledge base quality assessment. The hybrid approach demonstrates measurable improvements in talent identification accuracy when compared to traditional subjective methods, establishing a quantitative foundation for evidence-based educational planning. The system offers schools a standardized capability assessment tool that reduces evaluation bias while optimizing resource allocation for personalized learning development. Educational institutions can implement the framework to support more objective decision-making in student guidance and curriculum planning, particularly valuable for Indonesia's evolving educational landscape that emphasizes individualized learning pathways
Keywords
Expert System ; Aptitude Assessment ; Talent Identification ; Certainty Factor ; Dempster-Shafer Theory ; Educational Analytics
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Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 5 No. 2 (2025)
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Section: Articles
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Published: %750 %e, %2025
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License: CC BY 4.0
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Copyright: © 2025 Authors
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DOI: 10.35870/ijsecs.v5i2.5169
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Teddy Setiady
Informatics Engineering Study Program, Faculty of Science and Technology, Universitas Islam Nahdlatul Ulama Jepara, Jepara Regency, Central Java Province, Indonesia
Gentur Wahyu Nyipto Wibowo
Informatics Engineering Study Program, Faculty of Science and Technology, Universitas Islam Nahdlatul Ulama Jepara, Jepara Regency, Central Java Province, Indonesia
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Pristiwanti, D., Badariah, B., Hidayat, S., & Dewi, R. S. (2022). Pengertian pendidikan. Jurnal Pendidikan Dan Konseling (JPDK), 4(6), 7911–7915. https://doi.org/10.31004/jpdk.v4i6.9498.
-
-
-
-
Alim, S., Lestari, P. P., & Rusliyawati, R. (2020). Sistem pakar diagnosa penyakit tanaman kakao menggunakan metode certainty factor pada kelompok tani PT Olam Indonesia (Cocoa) cabang Lampung. Jurnal Data Mining dan Sistem Informasi, 1(1). https://doi.org/10.33365/jdmsi.v1i1.798.
-
Saragih, R. (2020). Sistem pakar mengidentifikasi minat bakat anak dengan metode Certainty Factor (Studi kasus: Sekolah Bilingual Nasional Plus Permata Bangsa Binjai). ALGORITMA: Jurnal Ilmu Komputer dan Informatika, 4(2), 10–18. https://doi.org/10.30829/algoritma.v4i2.8517
-
Dia, Z., Hendriyani, Y., & Anwar, M. (2021). Rancang bangun tes minat dan bakat menggunakan teori multiple intelligences dan metode Certainty Factor. Voteteknika (Vocational Teknik Elektronika dan Informatika), 9(3), 32–40. https://doi.org/10.24036/voteteknika.v9i3.112682
-
Devaus, L., Amaliah, Y., & Gusmana, R. (2024). Sistem Pakar Dalam Penentuan Minat dan Bakat Anak Usia Taman Kanak-Kanak Menggunakan Metode Dempster Shafer. Journal of Big Data Analytic and Artificial Intelligence, 7(1), 21-27. https://doi.org/10.71302/jbidai.v7i1.53.
-
Baihaqi, H. A., & Junaedi, L. (2022). Sistem pakar penerimaan siswa baru sekolah dasar berdasarkan tingkat IQ menggunakan metode Dempster Shafer (studi kasus: Sekolah Dasar Luqman Al Hakim Surabaya). Just IT: Jurnal Sistem Informasi, Teknologi Informasi, dan Komputer, 12(2). https://doi.org/10.24853/justit.12.2.%25p.
-
Meniati, L., & Santoso, I. (2019). Sistem Pakar Mendiagnosa Penyakit Tanaman Kakao Menggunakan Metode Certainty Factor di Desa Pardomuan 2. Jurnal Cyber Tech, 2(11). https://doi.org/10.53513/jct.v2i11.3321.
-
-
-
-
-
Hapsari, M. M. (2022). Pedoman penelusuran minat dan bakat jenjang SMP. Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi. https://repositori.kemdikbud.go.id/26912/1/Pedoman%20Penelusuran%20Minat%20dan%20Bakat%20Jenjang%20SMP.pdf
-
Marcelina, D., Yulianti, E., & Mair, Z. R. (2022). Penerapan Metode Forward Chaining Pada Sistem Pakar Identifikasi Penyakit Tanaman Kelapa Sawit. Jurnal ilmiah informatika global, 13(2). https://doi.org/10.36982/jiig.v13i2.2299
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