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All Journal Al-Hijr: Journal of Adulearn World Journal International of Lingua and Technology Journal International Dakwah and Communication Pengabdian Jurnal Abdimas Journal Neosantara Hybrid Learning Journal of Islamic Education Students International Journal of Research in Counseling Journal of Moeslim Research Technik Journal of Loomingulisus ja Innovatsioon Techno Agriculturae Studium of Research Research of Scientia Naturalis Journal of Biomedical and Techno Nanomaterials Journal of Humanities Research Sustainability Journal of Educational Teaching and Trends
Sok, Vann
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Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Physics Social Sciences Other

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Innovative Approaches to Assessing Language Proficiency in Digital Learning Environments Suryanti, Suryanti; Sok, Vann; Dara, Sokha
Journal International of Lingua and 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/jiltech.v3i3.731

Abstract

The rapid advancement of digital technology has significantly impacted education, including language learning and assessment practices. Traditional methods of language proficiency assessment, which often rely on written tests, are no longer adequate to meet the needs of learners in digital learning environments. The emergence of digital tools and platforms provides new opportunities for more flexible, interactive, and personalized assessments that can capture a holistic picture of language proficiency. This research aims to explore innovative approaches to assessing language proficiency in digital learning environments, with a focus on integrating modern technologies such as artificial intelligence (AI) and machine learning into assessment practices. The study employs a mixed-methods approach, combining qualitative and quantitative data collection through surveys, interviews, and experimental implementation of digital assessment tools. Data is analyzed to evaluate the effectiveness of these tools in accurately assessing different dimensions of language proficiency, including speaking, listening, and writing skills. Results indicate that AI-powered assessments provide real-time feedback, promote learner engagement, and offer a more personalized learning experience. Additionally, digital environments enhance the authenticity of language tasks by simulating real-life communication scenarios. The conclusion of the study suggests that innovative digital approaches offer a more comprehensive and responsive assessment framework, aligning with the evolving needs of modern language learners. Future research should explore further refinement of these tools to ensure their accessibility and effectiveness across diverse learner populations.
Metaverse Learning Environments and Student Well-Being: A Longitudinal Study on The Impact of Immersive Educational Counseling Rais, Rinovian; Dwita, Alfiani; Rosidin, Rosidin; Sok, Vann
International Journal of Research in Counseling Vol. 3 No. 2 (2024)
Publisher : Yayasan Minang Darussalam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70363/ijrc.v3i2.265

Abstract

This longitudinal study investigates the influence of immersive educational counseling within metaverse learning environments on student well-being. As educational institutions increasingly integrate virtual and augmented reality technologies, understanding their effects on students’ mental health and academic performance is essential. The research focuses on a diverse cohort of students who participated in immersive counseling sessions designed to enhance emotional support, social engagement, and academic guidance. Data collection spanned two academic years, utilizing quantitative surveys, qualitative interviews, and performance metrics to assess changes in well-being and academic outcomes.Results reveal that students engaged in metaverse counseling exhibited significant improvements in emotional resilience, motivation, and overall academic performance compared to their peers receiving traditional counseling. Additionally, the immersive nature of the metaverse fostered a sense of community and belonging, which further contributed to enhanced well-being. This study underscores the transformative potential of metaverse environments in educational settings, advocating for the incorporation of innovative technologies to support student mental health and academic success.
The Use of Augmented Reality in History Education: A Study on Conceptual Understanding Effects Priyono, Cipto Duwi; Sok, Vann; Souza, Felipe
Journal Neosantara Hybrid Learning Vol. 2 No. 3 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jnhl.v2i3.1613

Abstract

Technology integration in education has opened new avenues for enhancing student engagement and learning outcomes. Augmented Reality (AR) is a technology that offers immersive and interactive learning experiences, particularly in subjects like history, where visual and spatial understanding is crucial. ws and teacher observations to gain deeper insights into the learning experiences. The results indicated a significant improvement in the conceptual understanding of history in the experimental group compared to the control group. Students using AR demonstrated a better ability to visualize historical events, understand complex historical contexts, and establish connections between historical periods. Qualitative data supported these findings, with students reporting higher engagement and enjoyment in learning history through AR. The study concludes that AR can significantly enhance conceptual understanding in history education. AR-based learning tools offer a promising alternative to traditional methods by providing immersive and interactive experiences that engage students and deepen their understanding of historical concepts. These findings suggest that integrating AR into history curricula can be a valuable strategy for improving educational outcomes.
The Role of Chatgpt as A Virtual Assistant in Increasing Student Learning Collaboration Dara, Chenda; Vann, Rithy; Sok, Vann
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.v3i4.847

Abstract

The rapid development of artificial intelligence (AI) has led to the integration of AI tools like ChatGPT into various sectors, including education. One of the most promising applications is the use of AI as a virtual assistant to enhance student collaboration and learning experiences. Traditional education methods often struggle to foster effective collaboration among students, particularly in large, diverse classrooms. This study aims to explore the role of ChatGPT as a virtual assistant in increasing student collaboration and enhancing the learning process. The primary objective is to evaluate how ChatGPT can assist students in collaborative learning tasks, promote peer interaction, and provide personalized support. A mixed-methods research design was employed, combining qualitative and quantitative data collection methods. The study involved 150 students from different academic disciplines, who were introduced to ChatGPT as a collaborative tool for group projects. Data was collected through surveys, interviews, and collaboration performance assessments. The results indicate that ChatGPT significantly improved student collaboration, with students reporting increased interaction, engagement, and productivity during group tasks. Additionally, ChatGPT’s personalized assistance helped students overcome knowledge gaps and foster a collaborative learning environment. This study concludes that ChatGPT can be an effective virtual assistant in enhancing student collaboration and improving overall learning outcomes, offering valuable insights into AI’s potential in education.
Community Service Program Care: Developing a Tahfidz House in Koto Baru Village Oza, Febri; Salam, Muhammad Yusuf; Sinta, Dasmawar; Sok, Vann
Pengabdian: Jurnal Abdimas Vol. 3 No. 2 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/abdimas.v3i2.1602

Abstract

ABSTRACTBackground. Community service program is a place for students to apply the knowledge and skills obtained in the lecture bench directly to the community. One form of community service carried out by community service program students is the development of tahfidz houses.Purpose. This study aims to explore the effectiveness of the community service program program in fostering Rumah Tahfidz to facilitate learning of the Qur'an and produce a generation of Qur'an memorizers.Method. This study uses a qualitative approach with case studies, involving data collection through participatory observation and in-depth interviews with community service program participants and the management of the Al-Qur'an Tahfidz House.Results. The results of this study indicate that the community service program is effective in improving understanding and memorization of the Qur'an among children, by increasing active participation in learning activities and religious life. Conclusion. The construction of a tahfidz house is one of the community service program programs that is useful and can be used as a model in implementing religious values in the daily lives of the younger generation.
The Role of Body Language in Islamic Public Speaking to Influence Audiences in the Digital Era Waliulu, Habiba; Sok, Vann; Rith, Vicheka
Journal International Dakwah and Communication Vol. 5 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/jidc.v5i1.895

Abstract

The digital era has significantly transformed public speaking, especially in Islamic discourse, where the influence of body language plays a crucial role in engaging and persuading audiences. Body language, encompassing gestures, facial expressions, posture, and eye contact, can enhance the effectiveness of spoken words and create a stronger connection between the speaker and the audience. This research explores the role of body language in Islamic public speaking, focusing on its impact on influencing audiences within the context of digital platforms such as webinars, podcasts, and live-streamed sermons. Using a qualitative research design, this study analyzes interviews with experienced Islamic speakers, audience feedback, and case studies of prominent Islamic public speaking events conducted in digital spaces. The findings reveal that effective body language significantly improves audience engagement, comprehension, and emotional connection, even in virtual settings. Speakers who utilized expressive gestures and appropriate posture were more successful in delivering their messages and retaining the audience’s attention. The study concludes that body language remains a key tool for enhancing Islamic public speaking, even in the digital age, where it contributes to the effectiveness of communication and strengthens the delivery of religious messages. These findings offer insights into improving the quality of Islamic discourse on digital platforms.
Development of Machine Learning Algorithms for Anomaly Detection in Internet of Things (IoT) Networks Rith, Vicheka; Sok, Vann; 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.v1i5.1560

Abstract

The proliferation of Internet of Things (IoT) devices has increased the vulnerability of networks to security threats, making anomaly detection essential for maintaining system integrity. Traditional security measures often fall short in identifying and mitigating complex attack patterns that can jeopardize IoT networks. This research aims to develop a machine learning algorithm specifically designed for anomaly detection in IoT environments. The goal is to enhance the ability to identify unusual behavior indicative of potential security breaches while minimizing false positives. A dataset comprising network traffic from various IoT devices was collected and preprocessed to extract relevant features. Several machine learning algorithms, including decision trees, support vector machines, and neural networks, were implemented and evaluated. Performance metrics such as accuracy, precision, recall, and F1-score were used to assess the effectiveness of each model. The results indicated that the proposed machine learning algorithm outperformed traditional methods, achieving an accuracy of 95% in detecting anomalies. The model demonstrated a significant reduction in false positives compared to existing techniques, thereby enhancing the reliability of anomaly detection in IoT networks. The research concludes that the developed machine learning algorithm is a robust solution for detecting anomalies in IoT environments. This advancement contributes to the field by providing an effective tool for improving security measures in the rapidly evolving landscape of IoT. Future work should focus on real-time implementation and further optimization of the algorithm to adapt to dynamic network conditions.
Analysis of factors that influence student creativity in solving mathematical problems Rith, Vicheka; Sok, Vann; Dara, Ravi
Journal of Loomingulisus ja Innovatsioon Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/innovatsioon.v1i4.1707

Abstract

Creativity in solving mathematical problems is a critical skill for students, enabling them to think innovatively and apply knowledge in diverse contexts. However, the development of mathematical creativity is influenced by various factors, including cognitive, environmental, and instructional aspects. Understanding these factors is essential to designing effective strategies to foster creativity in mathematics education. Despite its importance, there is limited research exploring the interplay of these factors in influencing student creativity. This study aims to analyze the factors that influence student creativity in solving mathematical problems and determine which factors have the most significant impact. A mixed-method approach was employed, involving 150 high school students from three schools. Data were collected using a creativity assessment test, a questionnaire on cognitive and environmental factors, and semi-structured interviews. Quantitative data were analyzed using regression analysis, while qualitative data were subjected to thematic analysis. The findings revealed that cognitive factors, such as critical thinking and prior knowledge, were the strongest predictors of mathematical creativity. Environmental factors, including classroom climate and teacher support, also played a significant role. Instructional methods, particularly problem-based learning, were found to enhance creativity by encouraging exploration and independent thinking. The study highlights the multifaceted nature of mathematical creativity and the need for comprehensive strategies that address cognitive, environmental, and instructional factors to foster creativity in mathematics education.
Applications of Artificial Intelligence in Weather Prediction and Agricultural Risk Management in India Fawait, Aldi Bastiatul; Aprilani, Puteri; Sugiarto, Sugiarto; Sok, Vann
Techno Agriculturae Studium of Research Vol. 1 No. 3 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v1i3.1591

Abstract

Agriculture in India is particularly vulnerable to climate change and extreme weather conditions, which can negatively impact productivity and food security. This research was conducted against the background of the importance of developing technology to help farmers in dealing with weather uncertainty and managing agricultural risks. The purpose of this study is to explore the application of artificial intelligence (AI) in accurately predicting weather as well as managing the risks associated with extreme weather in India's agricultural sector. This study uses a descriptive method with a quantitative and qualitative approach, where data is collected through interviews with agricultural experts, analysis of historical weather data, and AI modeling. The results show that the AI application is able to predict weather patterns with an accuracy rate of up to 90%, which helps farmers make more informed decisions regarding planting timing, irrigation, and pesticide use. In addition, AI-based risk management systems allow for early detection of extreme weather, thereby reducing crop losses. The conclusion of the study is that artificial intelligence applications have great potential to improve food security and agricultural productivity in India by helping farmers anticipate weather changes and manage risks more efficiently. However, the adoption of this technology requires adequate training and infrastructure to ensure its optimal use in the field.
Nanostructured Catalysts for Efficient Energy Conversion: Recent Advances Vann, Rithy; Dara, Ravi; Sok, Vann
Research of Scientia Naturalis Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v1i4.1573

Abstract

The global transition towards sustainable energy sources has driven significant research into developing advanced catalytic materials that can enable efficient energy conversion processes. Nanostructured catalysts, with their unique physiochemical properties, have emerged as promising candidates to address the challenges associated with energy conversion technologies, such as low conversion efficiencies and high production costs. Understanding the recent advancements in the field of nanostructured catalysts is crucial for accelerating the development of next-generation energy conversion systems. This review article aims to provide a comprehensive overview of the recent progress in the design, synthesis, and application of nanostructured catalysts for efficient energy conversion. The study investigates the underlying principles governing the enhanced catalytic performance of nanomaterials and examines their potential impact on diverse energy conversion processes, including fuel cells, water splitting, and photocatalytic systems. The research methodology involves an extensive literature review of peer-reviewed journal articles, conference proceedings, and patent documents published within the last five years. The analysis focuses on the latest developments in the synthesis and characterization of nanostructured catalysts, as well as their performance evaluation under realistic operating conditions. The review highlights the successful implementation of various nanostructured catalyst architectures, such as nanoparticles, nanotubes, nanosheets, and core-shell structures, in enhancing the catalytic activity, selectivity, and stability for energy conversion applications. Significant advancements in the rational design of catalysts through the control of composition, morphology, and surface properties are discussed, along with their impact on improving energy conversion efficiencies and reducing production costs. The study concludes that the continued development of nanostructured catalysts holds great promise for addressing the current challenges in energy conversion technologies. The insights gained from this review can guide future research directions and facilitate the translation of nanostructured catalyst innovations into practical, large-scale energy conversion systems.
Co-Authors Aldi Bastiatul Fawait Fawait Aminatul Sholikah, Alfina Arnes Yuli Vandika Dara, Chenda Dara, Ravi Dara, Sokha Dwita, Alfiani Fauziyah, Cicik Judijanto, Loso Krit, Ponghi Muhammad Yusuf Salam Nabila, Nabila NUR RAHMI, SRI Oza, Febri Priyono, Cipto Duwi PUTERI APRILANI Rachma Hasibuan Rais, Rinovian Rith, Vicheka Rosidin Rosidin Salmiah Salmiah Sinta, Dasmawar Siti Jenar, Mauly Souza, Felipe Sugiarto S Suryanti Vann, Rithy Waliulu, Habiba Zahrotunnisa, Amalia