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All Journal Journal of Loomingulisus ja Innovatsioon Research of Scientia Naturalis Scientechno: Journal of Science and Technology Lingeduca: Journal of Language and Education Studies Journal of World Future Medicine, Health and Nursing Journal Emerging Technologies in Education
Ardi Azhar Nampira
Institut Teknologi Sepuluh November
Religion Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Environmental Science Law, Crime, Criminology & Criminal Justice Physics Other

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Design Thinking in STEM Classrooms: A Mixed-Methods Study on Enhancing Student Creativity Ninik Sri Rahayu; Nurul Huda; Ira Wulan Sari; Ardi Azhar Nampira
Journal of Loomingulisus ja Innovatsioon Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/innovatsioon.v2i3.2355

Abstract

Fostering creativity within Science, Technology, Engineering, and Mathematics (STEM) education remains a critical challenge, as traditional pedagogies often prioritize convergent thinking over innovative problem-solving. This study investigates the impact of integrating design thinking methodologies into STEM classrooms to enhance student creativity. The primary objective was to quantitatively measure changes in students’ creative abilities and to qualitatively explore their experiences and perceptions of the design thinking process. This research employed a sequential explanatory mixed-methods design. Initially, 120 secondary school students participated in a quasi-experimental study, completing pre-and-post Torrance Tests of Creative Thinking (TTCT). Subsequently, semi-structured interviews were conducted with a purposive sample of 20 students to provide deeper insights into the quantitative results. The findings revealed a statistically significant increase in students’ TTCT scores, particularly in the dimensions of fluency and originality. In conclusion, the integration of design thinking presents a robust pedagogical framework for systematically nurturing creativity in STEM disciplines, equipping students with essential skills for future innovation.    
AI-Augmented Creative Writing: Evaluating Machine-Human Collaboration in Narrative Innovation Ardi Azhar Nampira; Zhang Li; Wang Jing
Journal of Loomingulisus ja Innovatsioon Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/innovatsioon.v2i3.2357

Abstract

This study examines how artificial intelligence (AI) can augment human creativity in the field of narrative writing through a collaborative approach. The research addresses the growing influence of AI-based tools in creative industries and the need to understand their role in enhancing innovation rather than replacing human authorship. The study aims to evaluate the effectiveness of machine-human collaboration in generating original and innovative storylines. Using a mixed-methods design, twenty creative writing teams were engaged in structured workshops combining generative AI tools with traditional writing processes. Data were collected from narrative outputs, participant observations, and post-workshop interviews, and analyzed using thematic coding and comparative quality assessment. Findings indicate that AI-assisted teams produced more diverse narrative structures and demonstrated a significant increase in creative risk-taking compared to control groups. The results suggest that AI can serve as a valuable co-creator when guided by intentional human direction. This research concludes that rather than replacing writers, AI technologies can strengthen creative processes, supporting a hybrid model where human judgment shapes and refines machine-generated contributions.  
REAL-TIME SENSING OF AIRBORNE POLLUTANTS USING IOT-INTEGRATED ELECTROCHEMICAL SENSORS Ardi Azhar Nampira; Ming Pong; Siri Lek
Research of Scientia Naturalis Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i5.2383

Abstract

Air pollution poses a significant threat to public health, demanding effective real-time monitoring solutions. Traditional monitoring systems are often costly and sparsely located, limiting their spatial-temporal resolution. This study aimed to develop and validate a low-cost, IoT-integrated electrochemical sensor system for the real-time detection of key airborne pollutants. We fabricated electrochemical sensors for nitrogen dioxide (NO?), sulfur dioxide (SO?), and volatile organic compounds (VOCs), which were then integrated with a microcontroller and a wireless communication module. The system was calibrated and validated against reference instruments in both laboratory and field conditions. The developed sensors exhibited high sensitivity, good selectivity, and rapid response times (<60s). Field data demonstrated a strong correlation (R² > 0.92) with co-located reference-grade analyzers, and the IoT platform successfully provided continuous data visualization via a cloud dashboard. This study confirms that IoT-integrated electrochemical sensors provide a scalable and cost-effective solution for building dense, real-time air quality monitoring networks, offering significant potential for urban environmental management.
COMPARATIVE ANALYSIS OF SMART CATALYSTS FOR CO? REDUCTION: FROM MOLECULAR DESIGN TO LAB-SCALE PERFORMANCE Ardi Azhar Nampira; Clara Mendes; Tiago Costa
Research of Scientia Naturalis Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i4.2388

Abstract

The electrochemical reduction of carbon dioxide (CO?) is a critical strategy for mitigating climate change and producing value-added chemicals, yet the development of highly selective catalysts remains a primary challenge. This study aimed to conduct a rigorous comparative analysis of three distinct classes of "smart" catalysts a molecular cobalt complex, a metal-organic framework (MOF), and a single-atom copper catalyst (Cu-SAC) to elucidate the relationship between molecular design and lab-scale performance. The catalysts were synthesized, characterized via XRD and XAS, and evaluated for electrocatalytic CO? reduction in a flow cell reactor. The results showed that the Cu-SAC exhibited superior performance, achieving a Faradaic efficiency for ethylene (C?H?) exceeding 70% at a low cell voltage, significantly outperforming the MOF and molecular catalysts, which primarily produced CO and formate. This high selectivity was directly correlated with the optimized coordination environment of the isolated Cu sites. This comparative analysis confirms that rational design at the atomic level is a highly effective strategy for steering reaction pathways towards valuable multi-carbon products, providing a crucial benchmark for future catalyst development.
QUANTUM DOT-EMBEDDED POLYMER FILMS FOR FLEXIBLE PHOTONIC DEVICES: FABRICATION AND CHARACTERIZATION Ardi Azhar Nampira; Roya Zahir; Omar Khan; Siti Shofiah
Research of Scientia Naturalis Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i4.2389

Abstract

materials for photonic devices that can conform to non-planar surfaces. Quantum dots (QDs) are ideal candidates due to their size-tunable emission and high quantum yields, but their integration into durable, flexible platforms remains a key challenge. This study aimed to develop and characterize highly luminescent and mechanically flexible quantum dot-embedded polymer films as a robust platform for next-generation photonic applications. We fabricated composite films by embedding cadmium selenide/zinc sulfide (CdSe/ZnS) core-shell QDs into a polydimethylsiloxane (PDMS) polymer matrix via solution casting. The structural, optical, and mechanical properties were systematically investigated using transmission electron microscopy (TEM), UV-Vis absorption, photoluminescence (PL) spectroscopy, and cyclic bending tests. The results showed that TEM analysis confirmed a uniform dispersion of QDs within the PDMS matrix without aggregation. The composite films exhibited intense, stable photoluminescence, retaining the characteristic sharp emission of the colloidal QDs. Crucially, the films demonstrated exceptional mechanical flexibility, maintaining over 95% of their initial PL intensity after 1,000 bending cycles to a 5 mm radius. The optical properties remained stable under various strain conditions, proving the effective protection afforded by the polymer matrix. This work successfully demonstrates a scalable method for producing high-quality, flexible photonic materials.  
COMPUTATIONAL AND EXPERIMENTAL INSIGHTS INTO HYDROGEN STORAGE IN METAL-ORGANIC FRAMEWORKS (MOFs) Ardi Azhar Nampira; Ava Lee; Marcus Tan
Research of Scientia Naturalis Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i4.2390

Abstract

The transition to a hydrogen economy is critically dependent on the development of safe and efficient onboard hydrogen storage materials. Metal-Organic Frameworks (MOFs) have emerged as highly promising candidates due to their exceptionally high surface areas and tunable pore environments. This study aimed to combine computational modeling with experimental validation to elucidate the key structural factors governing hydrogen storage capacity in MOFs. A dual approach was employed, using Grand Canonical Monte Carlo (GCMC) simulations to predict hydrogen uptake in a series of MOFs with varying pore sizes and metal centers, followed by experimental synthesis and gas sorption analysis to validate the computational findings. The results revealed a strong correlation between the simulated and experimental data, confirming that both high surface area and optimal pore size (~10-15 Å) are crucial for maximizing physisorption. The GCMC simulations accurately predicted that MOFs with open metal sites exhibit enhanced hydrogen binding energies. This research concludes that a combined computational and experimental approach provides powerful predictive insights, confirming that tailoring pore geometry and introducing strong adsorption sites are key strategies for the rational design of next-generation MOFs for high-density hydrogen storage.    
Bionspired Photocatalysts for Green Hydrogrn Production: Toward Scalable Eco-Enengy Solutions Ardi Azhar Nampira; Lucas Lima; Thiago Rocha
Scientechno: Journal of Science and Technology Vol. 3 No. 3 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientechno.v3i3.3402

Abstract

In the pursuit of sustainable energy solutions, the development of green hydrogen production technologies has garnered significant attention. Photocatalytic water splitting is one of the most promising methods to generate hydrogen using solar energy. This study focuses on bioinspired photocatalysts for green hydrogen production, aiming to enhance the efficiency and scalability of photocatalytic processes. The research explores the principles behind bioinspired photocatalysts, which mimic the natural processes of photosynthesis in plants, and their potential to provide eco-friendly energy solutions. The primary objective of this research is to investigate novel bioinspired photocatalysts for efficient hydrogen production under solar irradiation. A combination of experimental methods, including synthesis, characterization, and performance evaluation of photocatalysts, was used. The study employs various techniques, such as X-ray diffraction, UV-Vis absorption spectroscopy, and electrochemical tests, to assess the photocatalytic performance under simulated sunlight. The results reveal that the bioinspired photocatalysts exhibit significantly enhanced hydrogen production rates compared to traditional catalysts. Notably, the integration of natural materials such as plant-derived components improves the photocatalytic efficiency and stability. In conclusion, bioinspired photocatalysts hold great promise for large-scale green hydrogen production, offering a sustainable and cost-effective alternative to conventional energy solutions. Future research will focus on optimizing these catalysts for industrial applications.
AUGMENTED REALITY IN FOREIGN LANGUAGE LEARNING: ENCHANCING VOCABULARY ACQUISTION THROUGH IMMERSIVE EXPERIENCES Ardi Azhar Nampira; Rit Som; Som Chai; Utary Rustam
Lingeduca: Journal of Language and Education Studies Vol. 4 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/lingeduca.v4i3.3306

Abstract

Foreign language learning continues to face persistent challenges, particularly in vocabulary acquisition, which is often constrained by decontextualized instruction and limited learner engagement. Recent advances in educational technology suggest that augmented reality (AR) can offer immersive and interactive learning environments capable of addressing these limitations. This study aims to examine the effectiveness of augmented reality–based instruction in enhancing vocabulary acquisition among foreign language learners through immersive learning experiences. The research employed a quasi-experimental design involving an experimental group receiving AR-supported vocabulary instruction and a control group taught using conventional methods. Data were collected through pre-tests and post-tests, classroom observations, and learner perception questionnaires, and were analyzed using both descriptive and inferential statistical techniques. The findings indicate that learners exposed to augmented reality demonstrated significantly higher vocabulary gains, improved retention, and greater learning motivation compared to those in the control group. Qualitative data further revealed that immersive visual and contextual cues facilitated deeper semantic understanding and learner engagement. The study concludes that augmented reality is a pedagogically effective tool for foreign language vocabulary instruction, offering meaningful, context-rich learning experiences. These results suggest that integrating AR into foreign language curricula can substantially enhance vocabulary learning outcomes and learner motivation, while also supporting innovative, technology-enhanced pedagogical practices.
Social Isolation and Cognitive Decline in Aging Populations: AI-Powered Monitoring Systems for Early Detection Omar Khan; Clara Mendes; Marcus Tan; Ardi Azhar Nampira
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i4.2371

Abstract

Social isolation is a significant and modifiable risk factor for accelerated cognitive decline and dementia in aging populations. Traditional methods for detecting cognitive changes, such as clinical screenings, are often infrequent and fail to capture the subtle, early behavioral shifts that precede a formal diagnosis. This study aimed to develop and validate an artificial intelligence model designed for the early detection of cognitive decline by passively monitoring behavioral and vocal biomarkers of social isolation in older adults living independently. A 24-month, prospective longitudinal study was conducted with a cohort of 200 community-dwelling adults aged 70 and older. A suite of unobtrusive in-home sensors was used to passively collect data on movement patterns, social communication (frequency and duration of conversations), and computer/phone usage. The AI-powered system identified individuals who would later show clinically significant cognitive decline with an accuracy of 91% and a lead time of approximately 7 months before formal assessment. The model successfully distinguished between simple loneliness and the specific behavioral patterns of social withdrawal associated with cognitive impairment. AI-powered passive monitoring systems are a highly effective and ecologically valid tool for the pre-clinical detection of cognitive decline linked to social isolation.
Augmented Reality in STEM Education: Enhancing Conceptual Understanding and Learner Motivation Ardi Azhar Nampira; Sanjay Sharma; Dorji Wangchuk
Journal Emerging Technologies in Education Vol. 3 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jete.v3i3.3410

Abstract

Background. The rapid development of digital technologies has encouraged the integration of augmented reality (AR) in STEM education as a response to persistent challenges in conceptual understanding and learner motivation. Purpose. This study aims to examine the effectiveness of augmented reality in enhancing students’ conceptual understanding and learning motivation in STEM subjects. Method. The research employed a quasi-experimental design with a mixed-methods approach, involving experimental and control groups at the secondary and tertiary education levels. Quantitative data were collected through pre-test and post-test instruments measuring conceptual understanding and standardized motivation questionnaires, while qualitative data were obtained from observations and semi-structured interviews. Results. The findings indicate that students exposed to AR-based learning environments demonstrated significantly higher gains in conceptual understanding compared to those taught using conventional methods. Additionally, AR integration positively influenced learner motivation, particularly in terms of attention, relevance, and engagement during learning activities. Conclusion. The study concludes that augmented reality is an effective pedagogical tool for STEM education, as it supports deeper conceptual learning and fosters intrinsic motivation.
Co-Authors Ava Lee Chak Sothy Clara Mendes Dorji Wangchuk Ira Wulan Sari Lucas Lima Marcus Tan Ming Pong Ninik Sri Rahayu Wilujeng Nurul Huda Omar Khan Rit Som Roya Zahir Sanjay Sharma Siri Lek Siti Shofiah Sokha Dara Som Chai Thiago Rocha Tiago Costa Utary Rustam Wang Jing Zhang Li