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All Journal Jurnal Minfo Polgan (JMP) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
Nuranisah Nuranisah
Universitas Battuta
Religion Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science Mathematics Social Sciences

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Trustworthy NLP Systems for Educational Decision Support: A Human Centered AI Approach Subhan Hafiz Nanda Ginting; Ericky Benna Perolihin Manurung; Nuranisah Nuranisah; Dewi Wahyuni
Jurnal Minfo Polgan Vol. 15 No. 2 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i2.16492

Abstract

Advances in Natural Language Processing (NLP) in education have led to the development of decision support systems capable of processing textual data such as student essay responses, learning feedback, academic records, and evaluation documents. However, most previous research has focused on improving model accuracy, while aspects of trust, transparency, fairness, and human involvement in decision validation have not been a primary focus. This research aims to develop a framework for Trustworthy NLP Systems for Educational Decision Support based on a Human-Centered Artificial Intelligence approach that positions teachers, students, and educational policymakers as key actors in the system’s design, interpretation, and evaluation processes. The novelty of this research lies in the integration of four key dimensions explainability, fairness, reliability, and human oversight into the NLP system architecture to support more ethical, transparent, and accountable educational decisions. The research methodology employs an experimental approach involving stages of educational text data collection, data preprocessing, text representation, NLP-based modeling, model performance evaluation, and system trust analysis through Explainable AI and fairness evaluation. The developed system is not only designed to generate educational classifications or recommendations but also to provide explanations for the model’s decision-making basis, thereby enabling human verification. The expected outcome is the creation of a conceptual and technical NLP model capable of improving the quality of educational decision-making without compromising ethical principles, accountability, and user-centricity. This research contributes to strengthening the direction of educational NLP development that is not only computationally intelligent but also trustworthy, inclusive, and human-centered.
Enhancing University Students’ Image Processing Skills through Hybrid Google Colab Training on Image Histogram Analysis Supiyandi Supiyandi; Rahmi Hayati; Febriyansyah Ramadhan; Husni Mubarak; Nuranisah Nuranisah
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 2 (2026): Oktober 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i2.1721

Abstract

University students generally understand basic digital image concepts but rarely practise image processing computationally. This community service activity aimed to improve students’ image processing skills through hybrid training based on Google Colab and Python, focusing on image histogram analysis. The training was held on 26 September 2026 in a computer laboratory and involved 20 students of Information Technology Program (8 on-site, 12 online). The activity comprised needs identification, demonstration, hands-on practice with a shared Colab notebook, histogram analysis, evaluation, and follow-up. Outcomes were measured using a pre-test and post-test, a practical task rubric, and a response questionnaire. The mean score increased from 85 to 95 (10 points; 11.8%). Eighteen of 20 participants (90%) completed the histogram analysis task according to the rubric, comprising all on-site participants and 10 of 12 online participants. The questionnaire score reached 94%. Unstable internet connection was the main constraint and was mitigated through mobile tethering.
Integrating COBIT 2019 and ISO/IEC 27001 for Strengthening IT Governance and Information Security Hendry Hendry; Muhammad Noor Hasan Siregar; Deni Apriadi; Alfiarini Alfiarini; Nuranisah Nuranisah
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.40

Abstract

This study aims to develop and evaluate an integrated framework combining COBIT 2019 and ISO/IEC 27001 to enhance IT governance and information security management. Using a qualitative-descriptive approach, the research involved document analysis, expert interviews, and a case-based validation within a government institution. The integration process consisted of three phases: mapping, harmonization, and synthesis, which resulted in the development of the Integrated IT Governance and Security Framework (IGSF). The findings reveal a high degree of alignment between COBIT 2019’s governance domains and ISO/IEC 27001’s security control structures, forming a unified model that strengthens strategic alignment, risk management, and compliance. Expert validation confirmed that the IGSF facilitates better communication between governance and security teams, reduces redundancy, and enhances operational efficiency. The practical case study demonstrated improved coordination, documentation, and audit readiness following implementation. This study contributes to IT governance and information security literature by presenting a structured, adaptable framework that organizations can adopt to achieve both governance excellence and security resilience. The results also suggest potential for future quantitative evaluation to measure the impact of this integration on organizational performance and compliance outcomes.
Co-Authors ., Alfiarini Deni Apriadi Dewi Wahyuni Ericky Benna Perolihin Manurung Febriyansyah Ramadhan Hendry Husni Mubarak Muhammad Noor Hasan Siregar Rahmi Hayati Subhan Hafiz Nanda Ginting Supiyandi Supiyandi