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All Journal Journal of Noesantara Islamic Studies Journal of Biomedical and Techno Nanomaterials Journal of Social Entrepreneurship and Creative Technology Journal of Multidisciplinary Sustainability Asean Scientechno: Journal of Science and Technology Journal of Paddisengeng Technology Lingeduca: Journal of Language and Education Studies Journal of World Future Medicine, Health and Nursing Journal of Social Science Utilizing Technology
Sofia Lim
Singapore University of Technology and Design (SUTD)
Religion Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Library & Information Science Other

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CREATIVE TECHNOLOGY AS A DRIVER OF SOCIO-PRENEURSHIP: ENTREPRENEURIAL RESPONSES TO GLOBAL CHALLENGES Lucas Wong; Sofia Lim; Sarah Brown; Alimuddin Alimuddin
Journal of Social Entrepreneurship and Creative Technology Vol. 3 No. 2 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v3i2.3825

Abstract

The increasing complexity of global challenges such as poverty, climate change, and inequality has pushed marginalized communities to seek innovative solutions through entrepreneurship. Creative technologies like virtual reality (VR), augmented reality (AR), and mobile applications offer novel opportunities for socio-preneurship, enabling entrepreneurs to develop solutions that promote social, environmental, and economic sustainability. This study explores how creative technologies serve as a catalyst for socio-preneurship by examining the experiences of entrepreneurs in underserved regions who have integrated these technologies into their business models. The research aims to understand how these technologies empower entrepreneurs to overcome systemic barriers and create scalable solutions to global challenges. A mixed-methods approach was utilized, combining qualitative interviews and quantitative surveys to gather insights from 20 entrepreneurs across diverse sectors, including education, healthcare, and agriculture. The findings suggest that creative technology enhances business performance, expands market access, and strengthens community ties. Moreover, social capital was identified as a crucial factor in amplifying the impact of technology adoption. The study concludes that creative technology is essential for inclusive socio-preneurship, offering a pathway to address global challenges while fostering local economic and social development. Policy recommendations include supporting technological infrastructure and social networks for marginalized entrepreneurs to ensure sustainable growth.
Development of an Aptamer-Based Electrochemical Biosensor for Early Detection of Prostate Cancer Markers Sofia Lim; Marcus Tan; Ethan Tan
Journal of Biomedical and Techno Nanomaterials Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jbtn.v1i4.1811

Abstract

Prostate cancer is a leading malignancy in men, where early detection is critical for effective treatment. Current diagnostic methods, such as PSA tests, have limitations in sensitivity and specificity. To develop an aptamer-based electrochemical biosensor for the early detection of prostate cancer markers, aiming to improve diagnostic accuracy and speed. The study involved the design and optimization of aptamers through SELEX, integration with electrochemical sensors, and validation using prostate cancer cell lines and clinical samples. Instruments used include electrochemical workstations, HPLC, and mass spectrometry for characterization and evaluation. The developed biosensor demonstrated a detection limit of 0.1 ng/mL for PSA, with a response time of less than 10 minutes. High reproducibility was achieved with a coefficient of variation below 5%, and the biosensor showed significant specificity and stability in detecting PSA in various samples. The aptamer-based electrochemical biosensor offers a promising tool for the early detection of prostate cancer markers, providing higher sensitivity and specificity compared to traditional methods. Further clinical validation is necessary to confirm its efficacy and reliability in broader applications.
AI ASSISTED PERSONALIZED VACCINE DESIGN USING MULTI-OMICS CANCER DATA Khalil Zaman; Shazia Akhtar; Sofia Lim; Ardi Azhar Nampira
Journal of Biomedical and Techno Nanomaterials Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jbtn.v2i3.2381

Abstract

The development of personalized cancer vaccines represents a promising frontier in oncology, yet traditional approaches struggle with the complexity and volume of multi-omics data. This study addresses this challenge by introducing an AI-assisted framework for the design of personalized vaccines. The primary objective was to leverage machine learning models to identify and prioritize neoantigens from integrated genomic, transcriptomic, and proteomic data of cancer patients. The methodology involved a deep learning pipeline to analyze multi-omics datasets, predicting tumor-specific mutations and their immunogenicity. This was followed by an algorithm to select the most potent neoantigen peptides for vaccine formulation, optimizing for both MHC binding affinity and T-cell activation potential. Our results demonstrate that the AI-driven approach significantly improved the speed and accuracy of neoantigen identification compared to conventional methods. The framework successfully predicted a set of high-quality vaccine candidates for individual patients, which showed strong in silico binding to patient-specific MHC molecules. We conclude that this AI-assisted methodology provides a powerful and scalable solution for personalized vaccine design, accelerating the translation of multi-omics data into clinically actionable immunotherapies.
The Effect of Artificial Intelligence in Adaptive Learning on Improving Student Understanding in Elementary School Iin Almeina Loebis; Sofia Lim
Journal of Multidisciplinary Sustainability Asean Vol. 2 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v2i2.2240

Abstract

Background. Advances in artificial intelligence (AI) technology have presented various innovative opportunities in the world of education, especially in the development of adaptive learning systems. The diverse understanding of elementary school students and the need for appropriate learning approaches make AI-based learning a promising alternative to improving learning effectiveness. Purpose. This study aims to determine the effect of the application of artificial intelligence in adaptive learning systems on improving student understanding at the elementary school level. The main focus is to see how much this system contributes in accommodating differences in learning styles and students' ability to understand the subject matter. Method. The research method used was a pseudo-experiment with a pretest-posttest control group design. The study population consisted of grade V students at an elementary school in Indonesia, with purposive sampling techniques to determine the experimental and control groups. The instrument is in the form of a concept understanding test and observation of the learning process. Results. The results showed that students who learned with AI-based adaptive systems experienced a significant increase in understanding compared to the control group. The average posttest score of the experimental group was higher with a more even increase. Case studies also show higher learning engagement and increased student motivation. Conclusion. The conclusion of this study states that the application of AI in adaptive learning has great potential in improving student understanding, especially with a personalized approach to material and adjusted learning speed. This technology is able to effectively answer the challenge of differentiating learning at the elementary level.
The Contribution of Kalam in Resolving Contemporary Theological Controversies: A Study of Rational Debates Ali Mufron; Sofia Lim; Rachel Chan; Jasafat Jasafat
Journal of Noesantara Islamic Studies Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jnis.v2i1.1845

Abstract

The discipline of Kal?m (Islamic theology) has historically served as a framework for addressing theological controversies, utilizing rational discourse to harmonize scriptural interpretation with intellectual inquiry. In the modern era, theological debates concerning issues such as faith, ethics, and the reconciliation of science and religion have intensified, necessitating renewed exploration of Kal?m as a method for resolving these challenges. This study examines the contribution of Kal?m in addressing contemporary theological controversies through rational debates and intellectual engagement. A qualitative approach was employed, combining historical analysis and textual study of classical Kal?m works with case studies of modern applications in theological discourse. Data were collected through critical analysis of primary texts and interviews with contemporary theologians and scholars actively engaging in rational debates on theological issues. The findings demonstrate that Kal?m provides a robust intellectual foundation for navigating contemporary theological controversies. Its emphasis on rational argumentation fosters constructive dialogue between traditional Islamic perspectives and modern intellectual paradigms. The study concludes that Kal?m remains a vital tool for resolving contemporary theological controversies, bridging the gap between tradition and modernity.
INTEGRATING DIGITAL TWINS AND SYSTEMIC AI FOR PREDICTIVE MAINTENANCE OF NATIONAL CRITICAL INFRASTRUCTURE Lucas Wong; Sofia Lim; Rohan Kumar; Rustiyana Rustiyana
Scientechno: Journal of Science and Technology Vol. 4 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientechno.v4i3.2891

Abstract

National critical infrastructure, including energy, transportation, and communication systems, plays a vital role in sustaining modern society, yet failures within these systems can trigger severe economic, environmental, and security consequences. Conventional maintenance approaches often lack the capability to anticipate failures in complex and large-scale infrastructures. Recent advancements in Digital Twin technology and Artificial Intelligence (AI) provide innovative opportunities to enhance predictive maintenance and infrastructure resilience. This study aims to integrate Digital Twins with systemic AI to optimize predictive maintenance strategies for national critical infrastructure by leveraging real-time data and intelligent prediction mechanisms. The research employs a combined framework in which sensor-generated data from infrastructure components are continuously synchronized with Digital Twin models and analyzed using machine learning algorithms to monitor system conditions, simulate operational behavior, and predict potential failures. The proposed framework was implemented in a case study of a national energy grid to evaluate its effectiveness. The results indicate that the integrated system significantly improved predictive maintenance performance, achieving a 30% reduction in unplanned downtime and a 25% decrease in maintenance costs through accurate failure prediction and timely intervention. These findings demonstrate that the integration of Digital Twins and systemic AI offers a robust, scalable, and efficient solution for enhancing reliability, resilience, and sustainability in the management of national critical infrastructure.
Smart Curriculum Mapping: A Blockchain Approach to Transparent and Customizable Educational Pathways Chen Mei; Sofia Lim; Ananya Rao
Journal of Paddisengeng Technology Vol. 1 No. 3 (2025)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v1i3.199

Abstract

Background. Traditional curriculum mapping often faces challenges of transparency, flexibility, and personalization. Existing digital systems tend to be centralized, limiting stakeholder trust and adaptability in designing individualized learning trajectories. Blockchain technology offers an innovative solution to ensure transparency, immutability, and decentralized control over educational data, enabling both institutions and learners to co-create customizable educational pathways. Purpose. This study aimed to investigate the potential of blockchain-based smart curriculum mapping in fostering transparent governance of curricula and supporting adaptive learning designs. Specifically, it examined how blockchain can integrate institutional requirements with learner-driven customization while ensuring accountability and security. Method. Using a mixed-method design, the research engaged 210 university students and 45 lecturers across three higher education institutions. Data were collected through surveys, interviews, and prototype testing of a blockchain-enabled curriculum mapping platform. The findings were analyzed using statistical methods and thematic coding to evaluate user perceptions, system usability, and pedagogical impact. Results. The findings indicate that blockchain-based curriculum mapping enhances trust among stakeholders by ensuring transparent records of course progress and requirements. Students reported increased autonomy in designing personalized pathways, while lecturers emphasized the benefits of immutable documentation for accreditation and evaluation. However, challenges such as technical literacy and system scalability were also identified. Conclusion. This study highlights the transformative role of blockchain in curriculum management. By integrating transparency, security, and learner-centered customization, smart curriculum mapping offers a scalable model for future educational governance. The findings contribute to both educational technology innovation and institutional policy-making, offering pathways toward more accountable and personalized higher education systems.
Get to Know Artificial Intelligence in Epidemiology: Predicting and Controlling Communicable and Non Communicable Diseases Sofia Lim; Jaden Tan; Anggra Trisna Ajani
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i1.1902

Abstract

The increasing burden of both communicable and non-communicable diseases (NCDs) presents significant challenges for public health worldwide. The application of artificial intelligence (AI) in epidemiology has emerged as a promising tool for predicting, monitoring, and controlling the spread of these diseases. This study aims to explore the role of AI in enhancing epidemiological practices and improving public health outcomes. The research employs a systematic review methodology, analyzing 60 peer-reviewed articles on the integration of AI technologies in disease prediction and control. The findings indicate that AI, particularly machine learning (ML) algorithms, has demonstrated remarkable success in predicting disease outbreaks, identifying high-risk populations, and optimizing resource allocation. AI-driven tools have been effectively utilized in both communicable diseases, such as influenza and COVID-19, and NCDs, including diabetes and cardiovascular diseases. The study concludes that AI holds substantial potential for transforming epidemiological practices, offering more accurate forecasts and efficient interventions. However, challenges such as data privacy concerns and resource limitations in low-income settings need to be addressed. The research highlights the need for continued investment in AI technologies to strengthen global disease prevention and control efforts.
Blockchain for Social Trust: Rebuilding Transparency in Public Sector Transactions through DLT I Putu Astawa; Rachmat Prasetio; Sofia Lim
Journal of Social Science Utilizing Technology Vol. 3 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i2.2290

Abstract

Background. The erosion of public trust in government institutions has become a critical global concern, driven largely by persistent issues of corruption, inefficiency, and opaque administrative processes. Amid this trust deficit, blockchain technology—especially Distributed Ledger Technology (DLT)—has emerged as a promising tool to rebuild transparency, accountability, and citizen engagement in the public sector. Purpose. This study aims to examine how blockchain can be strategically implemented to restore social trust by enhancing transparency in public sector transactions. Method. This study uses a qualitative method supported by several case studies, this study analyzes the initiative of real world blockchain adoption in countries such as Estonia, the United Arab Emirates, and Indonesia. Data was collected through analysis of policy documents, expert interviews, and comparative evaluation of the DLT -based public administration framework. Results. The findings indicate that blockchain’s immutable and decentralized architecture significantly mitigates information asymmetry, reduces opportunities for fraud, and enables real-time auditing of government activities. Moreover, smart contract integration allows for automatic enforcement of public service agreements, further reinforcing institutional integrity. However, the study also highlights critical challenges such as legal uncertainties, technological literacy gaps, and resistance to institutional change that may hinder effective implementation. Conclusion. In conclusion, while blockchain is not a panacea for all governance issues, it presents a powerful foundation for restoring social trust when embedded within a broader ecosystem of legal reform, digital literacy, and civic participation. This research contributes to the growing discourse on digital governance by offering a conceptual and empirical basis for blockchain-enabled transparency in the public sector.
TEACHER IDENTITY AND PROFESSIONAL DEVELOPMENT IN DIGITAL-BASED ENGLISH LANGUAGE TEACHING CLASSROOMS Evi Martiningsih; Lucas Wong; Sofia Lim
Lingeduca: Journal of Language and Education Studies Vol. 5 No. 3 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/lingeduca.v5i3.4251

Abstract

Digital transformation has reshaped English Language Teaching (ELT), requiring teachers to reconstruct their professional identities while adapting to pedagogical technologies, learner expectations, and institutional demands. Teacher identity is shaped by digital competence, reflective practice, collaborative learning, and organizational support, making sustainable professional development essential for technology-enhanced language education. This study examined the relationship between teacher identity and professional development in digital-based ELT classrooms and identified factors that strengthen professional identity in digitally mediated environments. A sequential explanatory mixed-methods design involved 420 English teachers from primary, secondary, vocational, and higher education institutions. Quantitative data were analyzed using descriptive statistics, structural equation modeling, mediation, and moderation analyses, while qualitative data were gathered through interviews, classroom observations, reflective journals, focus group discussions, and document analysis. Findings showed that digital pedagogical competence predicted teacher identity, while reflective practice partially mediated the relationship between professional development participation and professional identity. Collaborative professional learning and institutional support strengthened instructional innovation, technological self-efficacy, and professional confidence. Sustainable teacher identity therefore develops through interaction among digital competence, reflective inquiry, organizational learning, and collaborative professional development, enhancing teachers’ adaptability, instructional quality, and long-term professional resilience in technology-rich educational settings.
Co-Authors Ali Mufron Alimuddin Alimuddin Ananya Rao Anggra Trisna Ajani Ardi Azhar Nampira Chen Mei Ethan Tan I Putu Astawa Iin Almeina Loebis Jaden Tan Jasafat Jasafat Khalil Zaman Lucas Wong Marcus Tan Martiningsih, Evi Rachel Chan Rachmat Prasetio Rohan Kumar Rustiyana, Rustiyana Sarah Brown Shazia Akhtar