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All Journal ADI Journal on Recent Innovation (AJRI) ADI Bisnis Digital Interdisiplin (ABDI Jurnal) International Transactions on Artificial Intelligence (ITALIC) Journal of Computer Science and Technology Application
Ikhsan, Ramiro Santiago
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Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Library & Information Science Other

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Journal : Journal of Computer Science and Technology Application

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AI and Big Data in Advancing Mathematical Literacy Cybersecurity’s Moderating Role Sumliyah; Wardono; Mariani, Scolastika; Budi Waluya, Stevanus; Pujiastuti, Emi; Ikhsan, Ramiro Santiago
CORISINTA Vol 2 No 2 (2025): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v2i2.109

Abstract

In today’s rapidly evolving digital landscape, mathematical literacy has emerged as a crucial competency for students navigating data-intensive environments. The integration of Artificial Intelligence (AI) and Big Data in education holds transformative potential to enhance personalized learning and support data-driven teaching strategies, yet it also raises critical concerns around Cybersecurity, particularly in safeguarding student data and ensuring trust in digital platforms. This study aims to analyze the effects of AI and Big Data on mathematical literacy, while examining the moderating role of Cybersecurity. Using a quantitative research approach, data were collected through a structured questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 3. The results indicate that both AI and Big Data have significant positive effects on students’ mathematical literacy, with Big Data exerting the strongest influence through its ability to provide deep insights into student performance. AI also contributes effectively by enabling real-time feedback, adaptive learning, and personalized instruction. Although Cybersecurity demonstrated a weaker direct effect on mathematical literacy, it remains an essential enabler of a secure digital learning environment, fostering user trust and system integrity. This research highlights the importance of aligning educational technology implementation with strong digital safeguards to maximize learning outcomes. The findings offer managerial implications for educational institutions to invest in intelligent learning platforms supported by robust cybersecurity protocols. Ultimately, the study reinforces the relevance of SDG 4: Quality Education, by promoting inclusive, safe, and tech-enhanced learning ecosystems suited for the demands of 21st-century education.  
AI Framework for Synthesizing Qualitative User Feedback A Literature Review Sitorus, Santa Lusianna; Dewi, Ratih Komala; Vika Febrian; Muhammad Faris Ariq; Ikhsan, Ramiro Santiago
CORISINTA Vol 3 No 1 (2026): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/r1yewe47

Abstract

The increasing reliance on user-centered design in digital product development has intensified the need for systematic approaches to transforming qualitative user feedback into actionable insights for UX and UI decision-making. Although qualitative feedback provides rich understanding of user motivations, frustrations, and contextual behaviors, product teams often face challenges such as data ambiguity, interpretive bias, information overload, and weak alignment between research outcomes and product strategy. This literature review aims to synthesize existing academic research and industry practices to propose a structured framework that bridges qualitative analysis and technology-driven product decisions. Using a qualitative research design based on framework analysis, this study reviews established methods including user interviews, usability testing, open-ended surveys, thematic analysis, and affinity-based synthesis. These approaches are integrated into a four-step framework consisting of feedback coding, theme identification, alignment with product objectives, and formulation of actionable insights. The findings of this review suggest that applying a structured synthesis process enhances analytical clarity, improves traceability between user feedback and design actions, and supports more consistent prioritization in UX/UI practices. Illustrative applications drawn from prior studies demonstrate how the framework can translate qualitative insights into concrete design recommendations without relying on empirical experimentation. This study concludes that qualitative user feedback delivers meaningful value only when processed through a systematic synthesis mechanism that connects user narratives with strategic and operational product decisions, providing a conceptual foundation for data-driven and AI-supported UX/UI design environments.
Co-Authors Abbas, Maulana Amroni, Amroni Budi Waluya, Stevanus Emi Pujiastuti Fitra Putri Oganda Harlis Setiyowati Marviola Hardini Muhammad Faris Ariq Mustofa Kamil, Mustofa Pasha, Lukita Po Abas Sunarya Pujiati, Tri Qurotul Aini Ratih Komala Dewi Scolastika Mariani Sihotang, Sondang Visiana Silawati, Nur Sitorus, Santa Lusianna Sumliyah, Sumliyah Vika Febrian Wardono