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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURIKOM (Jurnal Riset Komputer)
Sandra Jamu Kuryanti
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Penilaian Tingkat Kematangan Tata Kelola Teknologi Informasi Dengan Menggunakan Domain PO (Plan and Organise) Sandra Jamu Kuryanti
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 2 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i2.4837

Abstract

IT governance assessment is carried out with the hope that the maturity level of governance at PT. ASAHIMAS FLAT GLASS TBK Jakarta. The results of the assessment carried out show that every IT process in the PO domain is at level 2, namely at the Define Process stage. Gap analysis in the process generally has a maturity level at level 2, which management expectations are generally at level 4. The maturity index value obtained shows the level of maturity in each process. Furthermore, it is known that 100% of the total 10 IT COBIT domain PO processes are at maturity level 2, while the expectations are 4 so there is a gap in maturity level 2. There is a gap in the 10 control objectives at PT. ASAHIMAS FLAT GLASS TBK Jakarta, which is 10 gaps in the PO domain. The COBIT findings from the 10 gaps that must be adjusted are PO1, PO2, PO3, PO4, PO5, PO6, PO7, PO8, PO9, and PO10.
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 Cep Adiwihardja Khaila Anjani Meutya Febi Santoso