2025 ICIEST

Monkeypox, an infectious disease that is now easier to spread among people, must be modeled to help guide measures meant to control the infection. Although numerical methods help solve these models, problems with their accuracy and computational speed have not been resolved yet. In this study, the authors introduce a Modified Picard Iterative Method as a new approach to solve the monkeypox transmission model, which consists of eight nonlinear ordinary differential equations. This method is extra reliable, as it produces accurate solutions for both brief and long-term simulations similar to what the fourth-order Runge-Kutta method provides for all the time covered in the model. Offering an effective choice for classical numerical methods, the Modified Picard Iterative Method helps to discover insights about how monkeypox is spreading and improves the use of computational techniques in modeling infectious diseases.

Gamification is an effective method for engaging students and sustaining their interest in learning. Educational games like Bingo incorporate elements like points and badges to enrich the learning experience. Playing Bingo can enhance cognitive function, communication skills, and critical thinking by encouraging active learning rather than passive memorization. This study aimed to evaluate students' awareness at the PERMATA@Pintar Negara Centre regarding using Bingo as a teaching tool. The research was conducted through purposive sampling, involving an online survey with students aged 12 to 17. The results indicate that while many students play Bingo, most are unaware of its educational potential. Therefore, it is recommended that the elements of Bingo games be introduced in teaching and learning.

The study presents the development of the SU(2) operator model for entanglement classification within the Local Unitary (LU) protocol. The operator model was systematically designed, specifically tailored for the pure three-qubit quantum system to accurately identify the distinct classes of entanglement. By leveraging the special unitary group, SU(2), this operator model development benefits researchers to gain a better understanding of the essence of entangled states, assisting researchers in effectively harnessing them to numerous potential applications in quantum computing, quantum cryptography, quantum teleportation and other respective fields. Hence, the study contributes significantly to advancing quantum information science. Furthermore, the foundation of this study establishes a broad pathway for advancements and future innovation in quantum information science and technologies.

Metal matrix composite (MMC) has many advanced mechanical properties such as high wear resistance, less weight, high strength and stiffness, lower coefficient of thermal expansion and high thermal conductivity, which are widely used in the automotive, railway and aerospace industries. The main limitation in MMC application is difficult to machine, which leads to low production volumes and high machining costs. This study aims to investigate the surface integrity of metal matrix composites through the high-speed turning experiments. High cutting velocity with low feed rate were the dominant parameter associated with the surface roughness. Surface roughness as low as 0.20 micron was achieved at low feed rate of 0.10 mm/rev with high cutting velocity of 175 m/min on Al 6061/SiCp by solid coated (TiAlN) cemented carbide tool. Conversely, the lowest microhardness of 102 HV are obtained at high velocity of 200 m/min with feed rate of 0.10 mm/rev. The study concludes that high cutting velocity can effectively reduce surface roughness when machining difficult-to-cut materials. However, it is important to consider that reducing the feed rate can significantly increase the turning time. Additionally, flank wear and chip formation must be considered when selecting cutting parameters. Continuous and long chips that wrap around the machined surface can cause surface damage. This research demonstrates that hard turning is a viable alternative to grinding for achieving low surface roughness in MMCs, provided that the appropriate operating parameters are carefully selected.

This research seeks to develop an innovative 3D-printed biosensor for the rapid and accurate detection of Escherichia coli (E. coli) bacteria in water samples. The proposed biosensor will incorporate a flow cell design, which allows continuous monitoring and efficient detection of E. coli in real-time. The sensor will be fabricated using conductive polymer-based materials integrated with specific biological recognition elements to ensure high sensitivity and specificity. The 3D printing technology will be utilized to create a precise and reproducible flow cell structure, optimizing the sensor's functionality and scalability. The research will proceed through several key phases: designing and simulating the flow cell structure, selecting and functionalizing the sensing materials, fabricating the biosensor using 3D printing techniques, and conducting extensive testing with water samples containing various concentrations of E. coli. This research will establish a foundation for future advancements in portable and effective biosensing devices for early detection of bacterial contamination.

Fossil fuels contribute to air pollution and drive climate change. Transitioning to solar energy offers a cleaner alternative. Perovskite solar cells are a promising advancement, potentially exceeding silicon cell efficiencies with simpler, cost-effective manufacturing. This research demonstrates the feasibility of electricity generation using a solution-processed perovskite solar cell under low light in the room building. The fabricated cell achieved an open-circuit voltage of 1.49V and a short-circuit current density of 5.15 mA/cm². A maximum power conversion efficiency of 18.67% was obtained under only around 10% of actual one sun light intensity. Such a high obtained efficiency of solar cell fabricated using inexpensive materials under low light intensity has become our current work novelty. These results highlight the potential of cost-effective perovskite solar cells for indoor and ambient light energy harvesting, supporting a shift towards sustainable energy solutions.

Education in Indonesia with the advancement of technology and communication in the digital era is growing rapidly. The purpose of this study is to increase awareness of educators in Indonesia with communication technology that can be easily developed adaptively and tested. The research method with a qualitative approach, data collection through observation, interviews. The research location at Madrasah Aliyah Negeri 2 Cirebon City, November - December 2024. The research subjects consisted of Guidance and Counseling Teachers, Physics Teachers, Curriculum and 4 students of Class XII Mathematics and Science. The plus skills program is related to career decision making in 3 areas of expertise. The results of the study explain that the level of ability of educators as facilitators in the world of education is a central concept of collaboration to improve the ability to synergize in depth and develop the potential of educators in understanding the process and mechanisms of technology-based learning. The skills expected by students can increase academic potential in the field of expertise.

This mixed-methods study investigates political socialization among Malaysian youth, analyzing data from the Malaysian Youth Index 2023 (N=5,414) and 12 focus group discussions. Findings reveal a digital paradox where high social media engagement (92%) coexists with low political literacy (5.2/10), exacerbated by algorithmic echo chambers. Significant urban-rural disparities (18-point gap) persist due to unequal access to civic education and digital infrastructure. While digital activism is prevalent (43%), formal political participation remains low (6%). The study proposes a Hybrid Political Socialization Model integrating digital platforms, mentorship programs, and community hubs to enhance youth engagement. Key recommendations include: (1) curriculum reforms emphasizing critical digital literacy, (2) accelerated rural digital development, and (3) institutionalized youth cocreation in policymaking. These findings offer both theoretical insights into digital-era citizenship and practical strategies for strengthening youth political participation in Malaysia’s multicultural democracy.

This study explores the probabilistic thinking of a male undergraduate mathematics education student characterized by a masculine gender trait and a field-independent (FI) cognitive style. The subject, referred to as MLI (Male, Field-Independent), was selected through purposive sampling based on gender traits, results from the Group Embedded Figures Test (GEFT), and mathematical ability assessed through UTBK SBMPTN questions. Most students tested were classified as having moderate mathematical ability, and the MLI subject was selected accordingly. Using a descriptive qualitative approach with a case study design, the study aimed to analyze the subject’s approach to solving a probability problem involving binomial distribution. Data were gathered through a problem-solving task administered at the Faculty of Teacher Training and Education, Universitas Sembilanbelas November Kolaka. The data analysis process included data reduction, presentation, and conclusion drawing. Findings revealed that the MLI subject successfully applied Polya’s four-step problem-solving model understanding the problem, devising a plan, carrying out the plan, and looking back. Although formulas were not explicitly written, the subject demonstrated clear logical structure and accurate reasoning. Reflective thinking was confirmed through interviews. These results highlight the need to develop probabilistic thinking in mathematics education to support effective teaching and real-world decision-making.

The increasing prevalence of pathogenic Escherichia coli (E. coli) in water and food sources poses a significant threat to public health, necessitating the development of rapid and accurate biosensor detection methods such as aptamerbased biosensors due to their high specificity and sensitivity. Aptamers are nucleic acids that can bind with high affinity and specificity to a range of target molecules. In this study, 1,000 shuffled variants of a known aptamer (PDB ID: 2AU4) were generated and evaluated for stability using RNAfold and RNALfoldz based on minimum free energy (MFE). The five most stable sequences were selected and analyzed for their secondary and tertiary structures using RNAComposer. The target protein, Shiga toxin (Stx, PDB ID: 1C48), was modeled with AlphaFold 3 and validated through Ramachandran plot analysis. Molecular docking using the HDOCK server revealed aptamer-protein binding interactions, offering insights into the structural features that influence binding specificity and stability. In conclusion, this research bridges theory for future applications, thereby establishing a theoretical framework to support the future development of aptamer-based biosensors targeting E. coli O157:H7.

In this project, triisopropylsilylethynyl-pentacene (TIPS-pentacene) will be utilized as a semiconducting polymer matrix for the preparation of biosensors based on organic field-effect transistor (OFET) structure. A thin layer of TIPS-pentacene can be easily formed on a silicon substrate through solution processable technique. Through polymer blend method which allows synergistic combinations of stacking configurations of multiple polymers energy levels which will enhance overall charge transport. Novel pentacene derivatives will also be proposed using machine learning method and computational study for synthesizing new narrow energy band gap polymer matrix. Analytical techniques, such as ultraviolet-visible (UV-Vis) spectroscopy will be used in the characterization of the materials properties. The proposed biosensor based on integration of biological compound into OFET will facilitate the government.

This research investigates the impact of Artificial Intelligence (AI) and Experiential Learning (EL) on student engagement and creativity, moderated by the digital education ecosystem. The study employs a quantitative methodology, surveying 103 university students with AI-integrated learning experiences. Statistical analyses, including regression and ANOVA, reveal that both AI and EL significantly enhance student engagement, with EL having a slightly stronger effect. Engagement serves as a significant predictor of creativity. The study further highlights the moderating role of the digital ecosystem in amplifying the impact of engagement on creativity. These findings emphasize the importance of a robust digital ecosystem in optimizing AI and EL integration to foster creativity.

The School Transformation Intervention Plan (PinTas) and the Outcome Performance Planning Matrix (OPPM) are part of the Malaysian Ministry of Education's (MOE) efforts to transform the education system, particularly in achieving the goals and vision set out in the School Transformation 2025 (TS25) initiative. The purpose of this study is to investigate the impact of the implementation of PinTas and OPPM on teachers in a TS25 school in northern Malaysia. The study was conducted qualitatively and involved 5 respondents comprising the school's senior leadership team, who were selected through purposive random sampling. For the purpose of data collection, interviews and document analysis were carried out. Interview transcripts were analyzed manually. The results of the analysis revealed that school leaders demonstrated a positive attitude towards the implementation of TS25, which is considered an important step in improving the quality of education and school achievement. The availability of resources, teacher commitment, and support from higher education management influence the effectiveness of the use of PinTas and OPPM. PinTas and OPPM provide a clear framework for the planning and evaluation of management strategies and assist them in monitoring school progress in a more structured manner. This proves the positive function of PinTas and OPPM in improving school performance and quality through various structured and systematic interventions. The role of PinTas and OPPM should continue to be strengthened.