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All Journal JOIV : International Journal on Informatics Visualization Applied Information System and Management
Muhamad, Gilang Aulia
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Computer Science & IT Languange, Linguistic, Communication & Media

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Exploring the Capabilities of GPT Models in Drafting Course Assessments Based on Bloom’s Taxonomy Muhamad, Gilang Aulia; Alsulami, Bassma Saleh; Thabit, Khalid Omar
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2811

Abstract

The application of Generative Pre-trained Transformer (GPT) models is significantly essential in automating drafting course assessment based on Bloom’s Taxonomy, specifically GPT-3.5-turbo, GPT-4, and GPT-4o. Therefore, this study aimed to explore the interaction between Artificial Intelligence (AI) models and educational content using refined prompt engineering methods to enhance the accuracy and relevance of the generated questions. For the investigation, the processing 146 Course Learning Outcomes (CLOs) method was applied through each model using OpenAI Application Programming Interface (API). Metrics such as 'Accuracy', 'Precision', 'Recall', and 'F1 Score' were used to assess the performance of each model. The results showed that GPT-4 was suitable for complex course assessments, showing superior performance in delivering detailed and precise responses. A cost-effective solution was obtained using GPT-3.5-turbo for generating simpler course assessment, while GPT-4o provided a middle ground, balancing cost, and performance. The results showed the potential of AI to reduce the administrative burden on instructors by streamlining the creation and refinement of course assessments. The enhancement of course assessments was also facilitated by automation, thereby supporting more adaptive questions. The potential for broader AI integration into educational practices promised a transformative impact on traditional course assessment drafting methods, enabling more dynamic and educational experiences. Moreover, further studies were recommended to explore the ethical dimensions of AI in education, the ability to handle diverse tasks, as well as assess the long-term impacts on learning outcomes and educational equity.
Risk Management in IT Projects for Digital Banking: A Case Study of an Indonesian State-Owned Bank Wibowo, Aji Prastio; Raharjo, Teguh; Trisnawaty, Ni Wayan; Muhamad, Gilang Aulia; Faridy, Azka
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46123

Abstract

The increasing use of information technology in the banking industry has made it more difficult to manage risks in the digital projects of state-owned banks. This study aims to examine the risk management processes of a state-owned mortgage bank in Indonesia and how it manages the information technology risks in the digital banking project lifecycle. This qualitative research is based on content analysis of forty-three risk assessment documents, with thematic coding using ATLAS.ti. This research was further enriched through expert interviews and a quantitative survey conducted among 38 project stakeholders. Risks are defined in a hierarchical classification and mapped to project phases using the PMBOK. Identifying operational, compliance, and third-party risks is most pertinent in the execution and post-implementation phases. Additionally, there are pressing concerns, such as the potential for cyber threats, non-compliance with applicable laws and regulatory frameworks, integration issues, over-reliance on service vendors, and systemic dependence on external vendors. In this case, the study integrates PMBOK, ISO 31000:2018, and the insights of seasoned practitioners to create a singular holistic mitigation strategy. It comprises a risk prioritization matrix, phased actionable treatment plans for each defined stage, and robust governance and responsiveness enhancement mechanisms for high-risk reactive IT environments. The guidance is triangulated with sector-specific intelligence, thereby underscoring proactive risk governance through communication, vendor due diligence, dynamic control, and real-time accountability across boundaries scaffolding. Further single-initiative case studies, multi-institutional case studies, evolving longitudinal risk studies, and the application of AI and blockchain for predictive and autonomous risk steering in digital finance could enhance and refine this work. 
Co-Authors Alsulami, Bassma Saleh Faridy, Azka Raharjo, Teguh Thabit, Khalid Omar Trisnawaty, Ni Wayan Wibowo, Aji Prastio