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All Journal JURIKOM (Jurnal Riset Komputer) Switch: Jurnal Sains dan Teknologi Informasi
Khaila Anjani
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Peningkatan Literasi Digital Anak Melalui Penyuluhan Dunia Digital yang Aman dan Bijak di RT.002 RW.009, Kelurahan Kwitang Ade Suryadi; Ricki Sastra; Suharyanto Suharyanto; Siti Khotimatul Wildah; Siti Laila Wahyuni; Khaila Anjani; Siti Nurjanah; Muhamad Iqbal Irsyad
Switch : Jurnal Sains dan Teknologi Informasi Vol. 3 No. 4 (2025): Juli: Switch : Jurnal Sains dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/switch.v3i4.436

Abstract

This community service program aims to improve children's digital literacy in RT.002 RW.009, Kwitang Subdistrict through structured educational outreach. The method applied is a participatory action research approach, involving pre- and post-test assessments using a digital literacy questionnaire. The results showed a significant increase in the average literacy score from 55.3 (pre-test) to 82.6 (post-test), confirming the effectiveness of the intervention. Key improvements were observed in awareness of online safety, understanding of hoaxes, and ethical social media use. This initiative contributes to informed and secure digital behavior in urban communities.
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 Meutya Febi Santoso Muhamad Iqbal Irsyad Ricki Sastra Sandra Jamu Kuryanti Siti Khotimatul Wildah Siti Laila Wahyuni SITI NURJANAH SUHARYANTO SUHARYANTO