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Leveraging Big Data Analytics for Talent Management and Prediction in Human Resources Hariri, Ahmad; Prasetio, Rachmat; Al-Shammari, Abdullah; Kara, Sevda
Journal of Social Science Utilizing Technology Vol. 2 No. 4 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v2i4.1780

Background. The increasing complexity of workforce management in modern organizations has driven the adoption of innovative tools such as Big Data Analytics (BDA) in human resources (HR). Talent management, encompassing recruitment, retention, and performance evaluation, has become a critical focus for organizations aiming to maintain competitiveness. Big Data Analytics enables HR professionals to identify patterns, predict trends, and make data-driven decisions, enhancing talent management processes. Despite its potential, the application of BDA in HR faces challenges, including data integration, privacy concerns, and skill gaps. Purpose. This study explores the role of Big Data Analytics in improving talent management and prediction, focusing on its impact on decision-making and organizational outcomes. Method. A mixed-method research design was employed, incorporating quantitative analysis of HR metrics and qualitative insights from interviews with HR professionals. Data were collected from 15 organizations across diverse industries, analyzing employee performance, recruitment patterns, and turnover rates. Predictive models were developed using machine learning algorithms to forecast talent trends and inform HR strategies. Results. The findings revealed that BDA significantly improved talent acquisition and retention processes, with a 25% increase in recruitment efficiency and a 30% reduction in turnover rates. Predictive models accurately identified high-potential candidates and flagged at-risk employees, enabling proactive interventions. Challenges related to data privacy and technical expertise were highlighted as areas for improvement. Conclusion. The study concludes that leveraging Big Data Analytics transforms talent management by enabling evidence-based decision-making and predictive insights. Addressing implementation challenges and investing in skill development will maximize its potential in HR practices.

Leveraging Big Data Analytics for Talent Management and Prediction in Human Resources Hariri, Ahmad; Prasetio, Rachmat; Al-Shammari, Abdullah; Kara, Sevda
Journal of Social Science Utilizing Technology Vol. 2 No. 4 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v2i4.1780

Background. The increasing complexity of workforce management in modern organizations has driven the adoption of innovative tools such as Big Data Analytics (BDA) in human resources (HR). Talent management, encompassing recruitment, retention, and performance evaluation, has become a critical focus for organizations aiming to maintain competitiveness. Big Data Analytics enables HR professionals to identify patterns, predict trends, and make data-driven decisions, enhancing talent management processes. Despite its potential, the application of BDA in HR faces challenges, including data integration, privacy concerns, and skill gaps. Purpose. This study explores the role of Big Data Analytics in improving talent management and prediction, focusing on its impact on decision-making and organizational outcomes. Method. A mixed-method research design was employed, incorporating quantitative analysis of HR metrics and qualitative insights from interviews with HR professionals. Data were collected from 15 organizations across diverse industries, analyzing employee performance, recruitment patterns, and turnover rates. Predictive models were developed using machine learning algorithms to forecast talent trends and inform HR strategies. Results. The findings revealed that BDA significantly improved talent acquisition and retention processes, with a 25% increase in recruitment efficiency and a 30% reduction in turnover rates. Predictive models accurately identified high-potential candidates and flagged at-risk employees, enabling proactive interventions. Challenges related to data privacy and technical expertise were highlighted as areas for improvement. Conclusion. The study concludes that leveraging Big Data Analytics transforms talent management by enabling evidence-based decision-making and predictive insights. Addressing implementation challenges and investing in skill development will maximize its potential in HR practices.

Decentralized Peer Review and e-Assessment in Hybrid Learning: Blockchain as a Tool for Equitable Feedback Mechanisms Kara, Sevda; Arslan, Murat; Toprak, Zeynep
Journal Emerging Technologies in Education Vol. 3 No. 3 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jete.v3i3.2235

Background. The integrity and equity of assessment in hybrid learning environments have been increasingly challenged by issues of transparency, bias, and centralized control. Traditional peer review systems often lack traceability and accountability, leading to concerns about the fairness and credibility of formative feedback. Purpose. This study explores the application of blockchain technology as a decentralized infrastructure for peer review and e-assessment in hybrid learning contexts. The research aims to evaluate how blockchain-based systems can enhance feedback transparency, reviewer accountability, and student trust in digital assessment processes. Method. Employing a design-based research methodology, a prototype blockchain-enabled peer assessment platform was developed and tested with 92 university students across two hybrid courses. Quantitative and qualitative data were collected through platform analytics, student surveys, and focus group discussions. Results. The results demonstrate that blockchain-based systems can serve not only as secure ledgers but also as ethical architectures for equitable formative assessmentConclusion. The study concludes that blockchain offers a viable mechanism for building equitable, transparent, and tamper-resistant assessment systems in hybrid learning. The research contributes to the growing field of educational technology by introducing a scalable model for decentralized e-assessment.

Evaluation of the Effectiveness of Virtual Teaching Assistant in Online Collaborative Learning Erdogan, Aylin; Kara, Sevda; Y?lmaz, Hale
Al-Hijr: Journal of Adulearn World Vol. 3 No. 4 (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/alhijr.v3i4.859

The rise of online learning has introduced various tools and technologies aimed at enhancing the learning experience, with virtual teaching assistants (VTAs) being one of the most prominent innovations. VTAs can support both students and instructors by providing real-time feedback, answering questions, and facilitating collaboration in online environments. However, the effectiveness of VTAs in fostering successful online collaborative learning experiences remains underexplored. This study evaluates the effectiveness of VTAs in online collaborative learning environments, focusing on their impact on student engagement, collaboration, and academic performance. A mixed-methods research design was employed, combining quantitative data from student performance assessments with qualitative feedback from surveys and interviews. The study involved 200 students across multiple online courses that integrated a VTA to support collaborative activities. Data was collected over the course of a semester. The results indicate that the use of VTAs significantly enhanced student engagement and collaboration, leading to improved academic performance. Students in the experimental group showed a 15% increase in collaboration scores and a 20% improvement in academic performance compared to the control group. This study concludes that VTAs can play a crucial role in improving the effectiveness of online collaborative learning by fostering greater student interaction, providing timely support, and enhancing learning outcomes.

The Impact of Collaboration Tools on Student Learning Outcomes Busnawir, Busnawir; Kaya, Cemil; Kara, Sevda
Journal International Inspire Education Technology Vol. 4 No. 1 (2025)
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.v4i1.785

The integration of digital collaboration tools in education has transformed the way students engage with learning materials and interact with peers and instructors. Traditional learning environments often limit real-time collaboration, critical thinking, and engagement, leading to challenges in student comprehension and retention. The increasing reliance on online learning platforms necessitates an evaluation of the effectiveness of collaboration tools in improving student learning outcomes. This study aims to examine the impact of digital collaboration tools on student performance, engagement, and knowledge retention in various educational settings. A mixed-methods approach was employed, combining quantitative analysis of student performance data with qualitative insights from surveys and interviews with educators and students. Findings indicate that the use of collaboration tools significantly enhances student engagement, promotes active learning, and improves academic performance. Tools such as shared documents, discussion forums, and real-time collaboration platforms foster interactive learning experiences, leading to increased knowledge retention. The study concludes that implementing well-designed collaboration tools within instructional frameworks positively influences student learning outcomes. Future research should explore the long-term effects of collaboration tools across diverse disciplines and assess their role in fostering higher-order thinking skills and problem-solving abilities.

The Impact of Using Learning Applications on the Cognitive Abilities of School-Age Children Putri, Agustin Andhika; Kaya, Cemil; Kara, Sevda; Nampira, Ardi Azhar
World Psychology Vol. 4 No. 1 (2025)
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/wp.v4i1.812

The use of digital learning applications has become increasingly prevalent in educational settings, offering a range of interactive tools designed to enhance student engagement and learning outcomes. As technology continues to influence education, it is essential to explore its impact on children’s cognitive abilities, particularly in school-age children. Learning applications are believed to improve cognitive functions such as memory, attention, problem-solving, and critical thinking. However, empirical evidence regarding the effects of these applications on children’s cognitive development remains limited. This study aims to investigate the impact of using learning applications on the cognitive abilities of school-age children. A quasi-experimental design was employed, involving 200 school-age children aged 6-12 years. The children were divided into an experimental group, using learning applications for 12 weeks, and a control group, which continued with traditional learning methods. Cognitive abilities were assessed before and after the intervention using standardized tests measuring attention, memory, and problem-solving skills. The results indicated that children in the experimental group showed significant improvements in cognitive abilities compared to the control group, particularly in memory and problem-solving skills. The study concludes that the use of learning applications positively influences cognitive development in school-age children, providing evidence for the integration of digital tools in educational practices to support cognitive growth.

Quantum Measurement Problems and Proposed Solutions Kaya, Cemil; Kara, Sevda; Ali, Mohammad
Journal of Tecnologia Quantica Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i3.1966

The problem of quantum measurements has become one of the most controversial topics in quantum physics. Various interpretations of the role of observers and measurement processes in the quantum world have been proposed, but there is no clear consensus yet. The study focuses on the various proposed solutions to quantum measurement problems, highlighting the theory of decoherence and Many Worlds as promising alternatives. The purpose of this study is to analyze the various proposed solutions to quantum measurement problems and explore the relevance of decoherence theory and Many Worlds in explaining measurements without directly involving observers. The method used in this study is a literature analysis of 30 leading publications that discuss the topic of quantum measurement problems and proposed solutions. The data collected included theoretical and experimental studies relevant to Copenhagen's interpretation, Many Worlds, and decoherence theory. The study found that Copenhagen's interpretation continues to dominate the literature, but approaches such as Many Worlds and decoherence are gaining more attention. Decoherence theory in particular offers a more adequate explanation for bridging the gap between the quantum world and the classical world without requiring the role of an observer in measurement. The study concludes that although many solutions have been proposed, decoherence theory provides a more cohesive and comprehensive alternative in addressing quantum measurement problems. Further research is needed to test the reliability of these theories in more controlled quantum experiments.

Role of the Gut Microbiome in the Pathogenesis of Crohn’s Disease Demir, Ahmet; Kara, Sevda; Khamraev, Javlonbek
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.v2i2.2022

Crohn's disease is one of the inflammatory bowel diseases (IBD) whose pathogenesis is still not fully understood. Many studies have shown a link between dysbiosis of the gut microbiome and the development of the disease. However, the specific mechanism linking the microbiota to inflammation in Crohn's disease is still open to further exploration. This study aims to investigate the role of the gut microbiome in the pathogenesis of Crohn's disease, specifically in differentiating the composition of the microbiota in patients with active disease and in remission. This study used a cross-sectional design with a sample of 100 patients diagnosed with Crohn's disease. Fecal samples were collected and analyzed using metagenomic techniques (16S rRNA sequencing) to identify the composition of the microbiota. Analysis of inflammatory biomarkers such as C-reactive protein (CRP) is also performed to assess disease status. The results showed that patients with active disease had a decrease in the number of anti-inflammatory bacteria such as Faecalibacterium prausnitzii and an increase in pathogenic bacteria such as Escherichia coli. In addition, there was a correlation between microbiome dysbiosis and increased CRP levels in patients with active disease. Microbiome dysbiosis has an important role in exacerbating the symptoms of Crohn's disease. This study provides evidence that the management of the gut microbiota can be a new therapeutic approach in the treatment of Crohn's disease.

SOIL QUALITY MONITORING TECHNOLOGY WITH IOT SENSORS IN NORWAY Yildiz, Emine; Akbulut, Baran; Kara, Sevda
Techno Agriculturae Studium of Research Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v2i4.2002

Internet of Things (IoT)-based soil quality monitoring technology presents new opportunities in sustainable agricultural management, especially in countries with extreme climatic conditions such as Norway. This study aims to evaluate the effectiveness of the use of IoT sensors in monitoring soil quality in real-time and its impact on agricultural productivity. A quasi-experimental research design was used by comparing a group that used IoT sensors and a control group that used traditional methods. The results show that the use of IoT improves the stability of soil moisture, temperature, pH, and nutrient levels, as well as reduces the waste of water and fertilizer. Farmers who used this technology reported a 15% increase in productivity compared to the control group. In conclusion, IoT technology has proven to be effective in improving land management efficiency and supporting sustainable agriculture, although infrastructure-related challenges still need to be addressed.

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