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All Journal Journal International Inspire Education Technology (JIIET) Journal Markcount Finance International Journal of Educational Narratives Journal of Moeslim Research Technik Journal of Selvicoltura Asean Journal of Tecnologia Quantica Journal of Loomingulisus ja Innovatsioon Research of Scientia Naturalis Journal of Biomedical and Techno Nanomaterials
Akhtar, Shazia
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Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Physics Social Sciences Other

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Effectiveness of Gamified Learning Strategies in Secondary Education Purwanti, Rina; Akhtar, Shazia; Mokoena, Lesedi
Journal International Inspire Education Technology Vol. 3 No. 3 (2024)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/jiiet.v3i3.725

Abstract

Gamified learning strategies have gained popularity in secondary education as a method to boost student engagement, motivation, and learning outcomes. In an era where technology and interactivity increasingly shape educational environments, gamification offers a unique approach by integrating game elements like points, badges, and leaderboards into the learning process. This research aims to assess the effectiveness of gamified learning strategies in improving academic performance, engagement, and motivation among secondary school students. A quasi-experimental design was used, involving two groups of students from three secondary schools: one utilizing a gamified learning approach and the other following traditional teaching methods. Data was collected through pre- and post-tests, engagement surveys, and interviews, allowing for both quantitative and qualitative analysis. The results showed that students in the gamified group demonstrated a 25% improvement in test scores and reported higher levels of engagement and motivation compared to the control group. The study concludes that gamified learning strategies can significantly enhance learning outcomes and student involvement in secondary education. These findings suggest that integrating game-based elements into curricula may create a more interactive and motivating learning environment, supporting academic growth. Further research is recommended to explore the long-term effects of gamification and its applicability across different subjects and educational levels.
Corporate Social Responsibility (CSR) and Cost of Capital: Evidence from the Indonesian Capital Market Budiasih, Yanti; Amin, Rafiullah; Akhtar, Shazia
Journal Markcount Finance Vol. 3 No. 1 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jmf.v3i1.2098

Abstract

Corporate Social Responsibility (CSR) has become a critical component of corporate strategy, with growing evidence suggesting its impact on financial performance and cost of capital. In Indonesia, where sustainable business practices are increasingly prioritized, understanding the relationship between CSR and cost of capital is essential for both firms and investors. This study examines the influence of CSR activities on the cost of capital for firms listed on the Indonesian Stock Exchange, focusing on how CSR initiatives affect investor perceptions and risk assessments. The research aims to provide empirical evidence on whether CSR can serve as a strategic tool to reduce the cost of capital and enhance firm value. Using a quantitative approach, this study analyzes financial data and CSR disclosures from 150 firms listed on the Indonesian Stock Exchange over a five-year period. Regression analysis is employed to assess the relationship between CSR performance and cost of capital, measured by weighted average cost of capital (WACC). The findings reveal that firms with higher CSR performance tend to have a lower cost of capital, indicating that CSR initiatives can reduce perceived risk and attract socially responsible investors. The study concludes that CSR activities positively influence the cost of capital, providing firms with a financial incentive to invest in sustainable practices. This research contributes to the discourse on CSR and corporate finance by offering practical insights for firms seeking to enhance their financial performance through responsible business practices.
The Influence of Parenting Patterns on the Mental Health of School-Age Children Shofwan, Arif Muzayin; Akhtar, Shazia; Amin, Rafiullah
International Journal of Educational Narratives Vol. 3 No. 1 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijen.v3i1.2152

Abstract

Background. Parenting patterns play a critical role in the mental health and well-being of children, particularly during the school-age years when they experience significant emotional and social development. The way parents interact with their children, provide support, and set boundaries can either foster resilience or contribute to mental health challenges. Purpose. This study examines the influence of various parenting patterns—authoritative, authoritarian, permissive, and neglectful—on the mental health of school-age children. Method. The primary objective is to investigate how these parenting styles affect children’s emotional regulation, self-esteem, anxiety levels, and overall mental well-being. A quantitative research design was employed, using surveys administered to 400 parents of school-age children, complemented by psychological assessments of their children’s mental health. Results. The results indicate that authoritative parenting is positively associated with better mental health outcomes, including higher self-esteem and lower anxiety levels. In contrast, authoritarian and neglectful parenting were linked to increased anxiety and lower emotional regulation in children. Conclusion. The study concludes that parenting patterns significantly influence the mental health of school-age children, highlighting the importance of supportive, balanced parenting approaches. Interventions aimed at promoting authoritative parenting could contribute to improved mental well-being in children, particularly in academic and social contexts.  
Effectiveness of Deep Learning Models in Cybercrime Prediction Mustofa, Muhammad; Akhtar, Shazia; Vandika, Arnes Yuli
Journal of Moeslim Research Technik Vol. 1 No. 5 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v1i5.1561

Abstract

The rise of cybercrime poses significant challenges to security agencies and organizations worldwide. Traditional methods of crime prediction often fall short in accurately identifying potential threats. As a result, there is a growing interest in leveraging advanced technologies, such as deep learning, to enhance predictive capabilities in cybersecurity. This research aims to evaluate the effectiveness of deep learning models in predicting cybercrime incidents. The study investigates how these models can improve accuracy and reliability compared to conventional prediction techniques. A dataset comprising historical cybercrime incidents was collected and preprocessed to extract relevant features. Various deep learning architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), were implemented. The models were trained and validated using a portion of the data, while performance metrics such as accuracy, precision, recall, and F1-score were used to assess their predictive capabilities. The findings indicate that deep learning models significantly outperform traditional methods in predicting cybercrime incidents. The best-performing model achieved an accuracy of 92%, showcasing its ability to identify complex patterns in the data. Additionally, deep learning models demonstrated lower false positive rates, enhancing their reliability in real-world applications. The research concludes that deep learning is a powerful tool for predicting cybercrime, offering enhanced accuracy and efficiency. These findings contribute to the field by highlighting the potential of advanced machine learning techniques in improving cybersecurity measures. Future work should focus on refining these models and exploring their applicability in real-time cyber threat detection.
Illegal Logging and Its Impact on Forest Ecosystems in Southeast Asia Aziz, Safiullah; Akhtar, Shazia; Amin, Rafiullah
Journal of Selvicoltura Asean Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsa.v1i4.1664

Abstract

Illegal logging poses a significant threat to forest ecosystems in Southeast Asia, compromising biodiversity, disrupting ecological balance, and undermining sustainable development efforts. The region's rich biodiversity and vital ecosystem services are increasingly jeopardized by unregulated logging practices, necessitating a thorough investigation of its impacts. This research aims to assess the extent of illegal logging in Southeast Asia and its effects on forest ecosystems. The study seeks to identify key drivers of illegal logging and analyze its implications for biodiversity and local communities. A mixed-methods approach was employed, combining quantitative data from satellite imagery and forest cover assessments with qualitative interviews of stakeholders, including local communities, government officials, and NGO representatives. Case studies from Indonesia, Malaysia, and Thailand were analyzed to provide insights into the dynamics of illegal logging. Findings reveal that illegal logging significantly contributes to deforestation and habitat loss, leading to declines in species populations and disruptions in ecosystem functions. Local communities reported negative impacts on their livelihoods and increased conflicts with wildlife as a result of habitat degradation. The study concludes that addressing illegal logging is crucial for the conservation of forest ecosystems in Southeast Asia. Effective governance, community engagement, and sustainable forest management practices are essential to combat illegal activities and protect biodiversity. Collaborative efforts among stakeholders will be vital for creating resilient forest ecosystems in the region.
Implementation of Quantum Error Correction Code on Qubit Superconducting to Improve Quantum Computing Stability Khan, Jamil; Akhtar, Shazia; Ali, Zara
Journal of Tecnologia Quantica Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v1i4.1681

Abstract

The background of this research focuses on the stability of quantum computing, which is a major challenge in the development of quantum technology. Superconducting qubits are known to be prone to errors due to environmental disturbances and noise, which hinders computational accuracy. Quantum error correction code (QECC) emerged as a solution to solve the problem by detecting and correcting errors that occur in qubits. This study aims to evaluate the application of QECC to superconducting qubits in improving the stability and accuracy of quantum computing. The method used was a quantitative experiment by comparing the qubit error rate before and after the implementation of QECC, with measurements on bit-flip, phase-flip, and decoherence errors. The results showed that the application of QECC successfully reduced the bit-flip and phase-flip error rates from 15.3% to 5.2% and 12.4% to 4.8%, respectively, while the decoherence decreased from 25.6% to 9.3%. These findings suggest that QECC can significantly improve the stability of quantum computing on superconducting qubits. The conclusion of this study is that the implementation of QECC can be an important step in improving efficiency and accuracy in quantum computing systems, although there are still limitations related to scalability and resources required for deployment in larger systems
Exploring Teacher Creativity in Developing Project-Based Learning Models in Indonesian Elementary Schools Raza, Amir; Akhtar, Shazia; Amin, Rafiullah
Journal of Loomingulisus ja Innovatsioon Vol. 1 No. 5 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/innovatsioon.v1i5.1709

Abstract

Teacher creativity plays a critical role in enhancing the quality of education, particularly in elementary schools. However, limited studies have explored how teachers develop innovative learning models tailored to students’ needs in the Indonesian context. This study aims to investigate the strategies employed by teachers to design project-based learning (PBL) models and assess their impact on students’ engagement and critical thinking skills. Employing a qualitative research method, data were collected through interviews, classroom observations, and document analysis involving 15 elementary school teachers across three regions in Indonesia. The findings reveal that teachers utilized diverse approaches, such as integrating local culture, leveraging digital tools, and fostering collaborative learning, to enrich PBL designs. Additionally, students exhibited increased motivation and improved problem-solving abilities when engaging in these models. However, challenges such as limited resources and training opportunities hindered optimal implementation. In conclusion, this study highlights the potential of teacher creativity in shaping effective PBL models and underscores the importance of institutional support for professional development. Future research should focus on scaling successful practices and addressing existing barriers.
Impact of Climate Change on Marine Biodiversity and Fisherie Prihadi, Donny Juliandri; Akhtar, Shazia; Ali, Zara
Research of Scientia Naturalis Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i1.2007

Abstract

Climate change poses significant threats to marine biodiversity and fisheries, impacting ecosystems and the livelihoods that depend on them. Rising sea temperatures, ocean acidification, and altered salinity levels are among the key environmental changes affecting marine life. Understanding these impacts is crucial for developing effective management strategies. This study aims to investigate the effects of climate change on marine biodiversity and the resulting implications for fisheries. The research seeks to identify vulnerable species and ecosystems, as well as assess the economic consequences for fishing communities. A comprehensive literature review was conducted, analyzing existing studies on climate change impacts on marine ecosystems. Data from various regions were synthesized to evaluate changes in species distribution, abundance, and community composition. Economic assessments of fisheries were incorporated to understand the socio-economic implications. Findings indicate significant shifts in marine biodiversity due to climate change, with some species migrating to cooler waters while others face population declines. These changes have direct implications for fisheries, leading to altered catch patterns and economic instability for fishing communities. Vulnerable species were identified, highlighting the need for targeted conservation efforts. This research underscores the urgent need for adaptive management strategies to mitigate the impacts of climate change on marine biodiversity and fisheries. Collaborative efforts between scientists, policymakers, and fishing communities are essential to ensure the sustainability of marine resources in the face of ongoing environmental changes.
AI-Assisted Personalized Vaccine Design Using Multi-Omics Cancer Data Zaman, Khalil; Akhtar, Shazia; Lim, Sofia; Nampira, Ardi Azhar
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.
FOREST-BASED LIVELIHOODS AND SOCIAL JUSTICE: AN ANALYSIS OF BENEFIT-SHARING MECHANISMS IN INDONESIA'S SOCIAL FORESTRY SCHEMES Judijanto, Loso; Amin, Rafiullah; Akhtar, Shazia
Journal of Selvicoltura Asean Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsa.v2i4.2485

Abstract

Social forestry programs are globally promoted as a key strategy, but their equitable outcomes are critical. Indonesia's ambitious social forestry agenda aims to reallocate millions of hectares, prompting this research to critically analyze benefit-sharing mechanisms across key schemes (Hutan Desa, HKm, Hutan Adat). The objective was to evaluate their effectiveness in promoting social justice and community livelihoods. This study employed a qualitative, multi-site case study approach, utilizing 120 interviews and policy analysis through a social justice framework. The findings reveal a significant gap between policy goals and reality: while land tenure improved, benefits often fail to be equitably distributed, being captured by local elites and marginalizing vulnerable groups. Furthermore, procedural justice remains weak due to limited community participation in decision-making. The novelty lies in this critical, justice-focused evaluation of Indonesia's national program. The implication is that for Indonesia's social forestry to succeed, a fundamental redesign of benefit-sharing mechanisms is required. Policy must explicitly embed distributive, procedural, and recognitional justice principles to ensure meaningful livelihood improvements for the poorest and most marginalized community members.
Co-Authors Ali, Zara Amin, Rafiullah Arif Muzayin Shofwan, Arif Muzayin Arnes Yuli Vandika Aziz, Safiullah Donny Juliandri Prihadi Judijanto, Loso Khan, Jamil Lim, Sofia Mokoena, Lesedi Muhammad Mustofa Nampira, Ardi Azhar purwanti, rina Raza, Amir Yanti Budiasih, Yanti Zaman, Khalil