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UNDERSTANDING EMPLOYEE BURNOUT: CAUSES, CONSEQUENCES, AND PREVENTION STRATEGIES Aung Myint; Nandar Hlaing; Kiran Pradhan
Research Psychologie, Orientation et Conseil Vol. 3 No. 2 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/rpoc.v3i2.3743

Employee burnout has become a significant concern for organizations worldwide, affecting both individual well-being and organizational productivity. Characterized by emotional exhaustion, depersonalization, and reduced personal accomplishment, burnout can lead to severe consequences such as increased absenteeism, decreased performance, and higher turnover rates. This study aims to examine the causes, consequences, and prevention strategies of employee burnout. The research explores the psychological, organizational, and environmental factors that contribute to burnout and investigates the impact of burnout on employee well-being and organizational outcomes. A mixed-methods approach was employed, combining quantitative surveys and qualitative interviews. Data were collected from 300 employees across various industries, using established scales to measure burnout, job satisfaction, and organizational commitment. The qualitative interviews provided deeper insights into personal experiences and the workplace factors contributing to burnout. The findings revealed that work overload, lack of control, and insufficient support were the primary causes of burnout. Burnout was found to significantly affect employee well-being, leading to increased stress, anxiety, and decreased job satisfaction. Prevention strategies, such as workload management and organizational support, were identified as effective in reducing burnout.

Quantum Computing to Design New More Effective Drugs Aung Myint; Nandar Hlaing; Zaw Min Oo
Journal of Tecnologia Quantica Vol. 1 No. 5 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v1i5.1698

The development of quantum computing provides great opportunities in various fields, one of which is in drug design. This technology offers a way to model molecular interactions more accurately and efficiently compared to conventional methods. This research aims to explore the potential of quantum computing in designing new drugs that are more effective by accelerating and improving precision in molecular simulations. This study aims to identify and evaluate the ability of quantum computing to design more effective drug compounds, as well as to understand how quantum simulation can improve the efficiency of the drug development process. The research method used is quantum simulation to analyze the interaction between compounds and biological targets. The selected compounds were analyzed using quantum algorithms to calculate bond energy and molecular stability. The results of the simulation are then compared with conventional drug design methods. The results show that quantum computing can model molecular interactions with more precision and efficiency. Compounds selected using quantum methods showed higher effectiveness, with stronger binding energies and more stable biological interactions compared to drug designs using classical methods. Quantum computing shows great potential in the design of new, more effective drugs. Although technical challenges still exist, especially in terms of hardware and algorithms, this research shows that these technologies can speed up and improve the drug design process. Further research is needed to overcome these limitations and optimize the application of quantum computing in the pharmaceutical field.

DEVELOPMENT OF A RECOMBINANT VACCINE TO PREVENT INFLUENZA VIRUS INFECTION Loso Judijanto; Aung Myint; Nandar Hlaing; Muntasir Muntasir
Journal of Biomedical and Techno Nanomaterials Vol. 2 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jbtn.v2i2.2025

Influenza virus remains a significant global health challenge, causing seasonal epidemics and potential pandemics with high morbidity and mortality rates. This study aims to develop a recombinant vaccine as a safer and more effective alternative to traditional influenza vaccines, which often suffer from limited efficacy and lengthy production timelines. Utilizing a recombinant DNA technology approach, this research employed the baculovirus expression system to produce hemagglutinin (HA) antigens derived from the influenza A virus. Experimental methods included antigen purification, immunogenicity assays in murine models, and neutralizing antibody titration. Results revealed that the recombinant HA vaccine elicited a robust immune response, with a significant increase in hemagglutination inhibition titers compared to control groups. Furthermore, the vaccinated subjects exhibited substantial protection against viral challenge, evidenced by reduced viral load and minimized lung pathology. The findings suggest that recombinant vaccine platforms offer promising avenues for rapid and scalable vaccine development. This study underscores the potential of recombinant influenza vaccines in mitigating future influenza outbreaks with improved safety, efficacy, and production agility.

The Quantified Self and Digital Piety: Analyzing Islamic Prayer Apps, Datafication, and their Impact on Daily Worship Nandar Hlaing; Aung Myint; Murat Arslan
Islamic Studies in the World Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/isw.v3i1.2699

The widespread adoption of Islamic prayer applications has introduced new forms of digital piety in which acts of worship become increasingly structured, quantified, and mediated through mobile technologies. The rise of these apps reflects broader cultural shifts toward datafication, self-tracking, and algorithmically guided religious practice. While prayer apps offer convenience, reminders, and personalized worship analytics, concerns have emerged regarding overreliance on digital tools, potential erosion of spiritual intentionality, and the implications of data extraction for user privacy. These dynamics highlight the need to critically examine how quantified self technologies shape Muslim devotional life. This study aims to analyze the influence of Islamic prayer apps on daily worship by investigating how datafication, algorithmic nudges, and quantified worship metrics affect users’ spiritual habits and perceptions of religious discipline. The research seeks to explore both the empowering and constraining effects of digital piety on contemporary Muslim practice. A mixed-methods approach was employed, combining a quantitative survey of 268 Muslim prayer app users with qualitative interviews involving twenty participants who regularly engage with worship-tracking features. Document analysis of popular prayer apps was also conducted to examine interface design, tracking mechanisms, and data-collection practices. Findings reveal that prayer apps significantly increase worship consistency, particularly in maintaining prayer schedules and tracking missed prayers. However, the quantification of worship introduces psychological dependence on reminders and metrics, shifting spiritual motivation from intrinsic intentionality to external digital cues. The study concludes that while prayer apps enhance ritual discipline, they also reshape devotional experiences through datafication, necessitating ethical reflection on privacy, autonomy, and the meaning of worship in a digital age.

Cryptocurrency Taxation Frameworks: Comparative Analysis Between the EU, US, and Southeast Asia Loso Judijanto; Aung Myint; Nandar Hlaing
Journal Markcount Finance Vol. 3 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jmf.v3i2.2578

The rapid growth of cryptocurrency markets has created unprecedented challenges for tax authorities worldwide, particularly in defining ownership, valuation, and jurisdictional liability for digital assets. Divergent taxation policies among major economies have produced inconsistencies in compliance, enforcement, and fiscal fairness. This study aims to conduct a comparative analysis of cryptocurrency taxation frameworks in the European Union (EU), the United States (US), and Southeast Asia, emphasizing their legal classifications, regulatory mechanisms, and fiscal implications. A qualitative comparative method was employed, combining policy document analysis, case law review, and secondary data synthesis from governmental and institutional reports. The findings reveal that the EU prioritizes harmonization through the Markets in Crypto-Assets (MiCA) regulation, the US applies a capital gains taxation model based on asset categorization, while Southeast Asian countries exhibit fragmented and evolving approaches influenced by institutional maturity. The analysis highlights that effective cryptocurrency taxation depends on transparency, interagency coordination, and digital infrastructure readiness. The study concludes that global policy coherence is essential to prevent tax arbitrage and ensure equitable fiscal governance in the digital economy. These results contribute to the development of a unified conceptual framework for cross-border digital asset taxation.

Artificial intelligence innovations in genetic technology: DNA-based diagnostics for the future of medicine Thandar Htwe; Aung Myint; Muntasir Muntasir
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i2.1908

Advancements in artificial intelligence (AI) are revolutionizing the field of genetic technology, particularly in DNA-based diagnostics, offering promising applications for the future of medicine. The rapid growth of AI in the analysis of genetic data allows for faster, more accurate, and cost-effective diagnostic processes. This study explores the integration of AI innovations in DNA diagnostics and their potential to transform clinical practices. Using a systematic review methodology, this research evaluates the current AI-driven genetic diagnostic technologies, focusing on their impact on disease detection, genetic mutation identification, and personalized treatment strategies. The findings reveal that AI-based tools, such as deep learning and machine learning algorithms, significantly improve the accuracy and speed of genetic diagnoses, particularly in rare genetic disorders and cancers. These technologies are also shown to enhance the predictive power of genetic tests, offering insights into patients' future health risks. The study concludes that AI-driven DNA diagnostics hold the potential to revolutionize medical practice, providing more precise, individualized care while reducing healthcare costs. However, challenges related to data privacy, algorithm transparency, and the need for large-scale clinical validation remain.

Mobile Health (mHealth) Applications: Transforming Preventive Health and Patient Engagement Aung Myint; Nandar Hlaing; Zaw Min Oo; Rustiyana Rustiyana
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i3.2930

The rapid expansion of mobile health (mHealth) applications has reshaped contemporary healthcare by enabling continuous preventive health management and enhancing patient engagement beyond traditional clinical settings. This study aims to examine how mHealth applications contribute to preventive health behaviors and patient engagement, with particular attention to usage patterns, behavioral outcomes, and contextual influences. A mixed-methods research design was employed, combining quantitative analysis of user surveys and application usage data with qualitative insights from interviews and a community-based case study. The findings reveal that frequent and sustained use of mHealth applications is associated with improved preventive behaviors, including increased physical activity, better dietary adherence, and enhanced medication compliance. The results also show that mHealth applications strengthen patient engagement by fostering greater health awareness, self-efficacy, and interaction with healthcare providers. However, variations in outcomes are influenced by digital literacy, personalization features, and the level of contextual support available to users. The study concludes that mHealth applications function as effective tools for transforming preventive health and patient engagement, but their impact depends on user-centered design and integration within broader health systems. The novelty of this research lies in its integrated analysis of preventive health outcomes and patient engagement within a single empirical framework, highlighting mHealth as a foundational component of modern, participatory preventive healthcare.

Social Media as Narrative Pedagogy: Instagram Stories and TikTok in Contemporary Learning Practices Misbahul Khairani; Aung Myint; Thandar Htwe; Siti Nur Azizah
International Journal of Educational Narratives Vol. 3 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijen.v3i6.2563

Background. The rapid evolution of social media platforms has reshaped educational communication, offering new spaces for narrative-based learning that merges visual storytelling with participatory engagement. Purpose. This study explores the use of Instagram Stories and TikTok as narrative pedagogical tools that enhance students’ reflective, creative, and critical learning experiences in contemporary classrooms. Method. The research aims to analyze how short-form digital narratives can foster multimodal literacy, social interaction, and emotional connection in learning processes. Employing a qualitative narrative inquiry design, data were collected through classroom observations, student-generated content, and semi-structured interviews with educators and learners across higher education contexts. Results. The findings reveal that Instagram and TikTok stories serve as dynamic platforms for constructing personalized learning narratives that integrate academic content with lived experiences. Students demonstrated heightened engagement, creativity, and agency when invited to design educational stories, while teachers reported improved dialogic relationships and inclusivity in their classrooms. Conclusion. The study concludes that narrative pedagogy through social media transforms passive consumption into active knowledge creation, bridging formal and informal learning spaces. It emphasizes the potential of digital storytelling to cultivate critical digital citizenship and empathy among learners in the 21st century.

From Distraction to Dialogue: A Narrative Analysis of Classroom Management as an Act of Co-Constructing Mutual Respect Laila Ngindana Zulfa; Sota Yamamoto; Aung Myint
International Journal of Educational Narratives Vol. 4 No. 3 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijen.v4i3.3964

Background. Classroom disruptions are often addressed through punitive or authoritarian strategies that suppress student agency rather than foster meaningful engagement. The prevailing discourse frames classroom management as a mechanism of control, largely neglecting its relational and dialogic dimensions. This study departs from that reductive view by examining how teachers and students collectively negotiate behavioral norms through sustained communicative interaction. Purpose. This study aims to explore how classroom management practices function as a co-constructive process through which mutual respect is dialogically produced between teachers and students. Method. A narrative inquiry design was employed, drawing on in-depth interviews, classroom observations, and reflective journals from six secondary school teachers across diverse institutional contexts. Data were analyzed through thematic narrative analysis, attending to relational episodes, turning points, and discursive patterns. Results. Findings reveal that effective classroom management transcends behavioral correction; it emerges as an ongoing, intersubjective dialogue in which teachers reframe disruptions as opportunities for relational repair and mutual recognition. Three narrative patterns were identified: repositioning authority through empathetic listening, transforming conflict into collaborative problem-solving, and sustaining respect through consistent communicative reciprocity. Conclusion. Classroom management, when approached dialogically, serves as a pedagogical act of co-constructing mutual respect rather than enforcing compliance. These findings call for a paradigmatic shift in teacher education toward relational and dialogic competencies.

The Effectiveness of Podcast-Based Learning for Improving Listening Skills: A Ubiquitous Learning Approach Yaredi Waruwu; Aung Myint; Nandar Hlaing
International Journal of Language and Ubiquitous Learning Vol. 3 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijlul.v3i6.3029

Background. The widespread availability of podcasts and the ubiquity of mobile devices enable learners to access diverse listening materials anytime and anywhere, making this approach highly suitable for ubiquitous learning. Purpose. This study aimed to evaluate the effectiveness of podcast-based learning in improving learners’ listening comprehension skills by employing a ubiquitous learning approach. It also sought to examine learners’ engagement and perceptions of the effectiveness of podcast-based learning compared to traditional listening instruction. Method. The research employed a quasi-experimental design involving two groups of learners. The experimental group used podcasts as the primary listening tool, while the control group relied on traditional listening methods. Results. The findings revealed a significant improvement in listening comprehension among learners in the podcast-based learning group compared to those in the control group. In addition, learners exposed to podcast-based learning reported higher levels of engagement, satisfaction, and perceived effectiveness than those using traditional methods. Conclusion. The study concludes that podcast-based learning is an effective and engaging tool for enhancing listening comprehension, particularly in contexts where traditional classroom-based learning is limited or not feasible.

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