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All Journal JURIKOM (Jurnal Riset Komputer)
Cep Adiwihardja
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Implementasi Model Gpt-3.5 Turbo Untuk Otomatisasi Penilaian Esai Pada Sistem Pembelajaran Daring Ade Suryadi; Sandra Jamu Kuryanti; Cep Adiwihardja; Khaila Anjani; Meutya Febi Santoso
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 6 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i6.9317

Abstract

Essay assessment in online learning requires significant time, effort, and consistency, which can be challenging to maintain when conducted manually. This study explores the use of the large language model GPT-3.5 Turbo as the core of an automated essay scoring system for online learning platforms. Employing a Research and Development (R&D) approach with the ADDIE development model—comprising Analysis, Design, Development, Implementation, and Evaluation phases—the research adopts the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework for its methodology. The automated essay scoring system utilizing Prompt 4 demonstrated exceptionally high accuracy and reliability. The model achieved an accuracy of 94.3%, an F1-Score of 0.955, and a Cohen’s Kappa value of 0.878. This high Kappa value indicates a very strong agreement between AI-generated assessments and the gold standard validated by educators, surpassing the initial inter-rater agreement among educators themselves, which was only 0.1157. The superior performance of Prompt 4 is also confirmed by the lowest Mean Absolute Error (MAE) of 30.54 and the highest Area Under the Curve (AUC) of 0.956.
Co-Authors Ade Suryadi Khaila Anjani Meutya Febi Santoso Sandra Jamu Kuryanti