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Nampira, Ardi Azhar
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The Effect of Digital Twin and Edge AI on Industrial Machine Maintenance Optimization in Karawang Saleh, Mohamad Zein; Nampira, Ardi Azhar; Iskandar, Yusuf
West Science Interdisciplinary Studies Vol. 3 No. 06 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i06.1988

Abstract

This study investigates the impact of Digital Twin and Edge AI technologies on optimizing industrial machine maintenance in Karawang, Indonesia. Using a quantitative research approach, data were collected from 80 respondents via a Likert-scale questionnaire and analyzed using SPSS version 25. The findings reveal significant positive relationships between both technologies and maintenance optimization. Digital Twin technology enhances predictive maintenance by enabling real-time simulations, while Edge AI improves decision-making through decentralized data processing. Together, they explain 58% of the variance in maintenance optimization. These results emphasize the synergistic effects of these technologies in reducing downtime, improving operational efficiency, and achieving cost savings. This research contributes to the understanding of advanced technological adoption in industrial maintenance and provides practical implications for enhancing productivity in industrial settings.
Bibliometric Review on Infrastructure Monitoring with IoT Judijanto, Loso; Justam, Justam; Nampira, Ardi Azhar
West Science Interdisciplinary Studies Vol. 3 No. 06 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i06.2013

Abstract

The integration of the Internet of Things (IoT) into infrastructure monitoring has transformed how built environments are observed, maintained, and managed. This study conducts a comprehensive bibliometric review to map the research landscape, thematic trends, and collaboration patterns in the domain of IoT-based infrastructure monitoring. Using data retrieved from the Scopus database (2010–2024) and analyzed through VOSviewer, the study identifies key research clusters, influential authors, prolific countries, and the evolution of core topics over time. Results show that the research focus has shifted from basic sensor deployment and data acquisition to advanced topics such as machine learning, edge computing, data privacy, and cybersecurity. India, China, and the United States emerge as leading contributors, with dense global collaboration networks. The study highlights both the maturity of core research areas and the emergence of new directions such as blockchain integration and privacy-preserving infrastructure systems. These findings provide valuable insights for academics, policymakers, and practitioners aiming to enhance infrastructure resilience and efficiency through IoT technologies.
Gamification and Student Motivation: Evaluating E-Learning Engagement from an Educational Psychology Perspective Sappaile, Baso Intang; Jenheri, Jenheri; Sari, Arum Fandan; Nampira, Ardi Azhar
Darussalam: Journal of Psychology and Educational Vol. 4 No. 1 (2025)
Publisher : Yayasan Minang Darussalam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70363/djpe.v4i1.308

Abstract

This study investigates the impact of gamification on student motivation and engagement in e-learning environments from an educational psychology perspective. The research aims to evaluate how game-based elements—such as points, badges, leaderboards, and challenges—affect intrinsic and extrinsic motivation, learning persistence, and cognitive engagement among students. Using a mixed-methods approach, data were collected through surveys, system analytics, and interviews involving 210 undergraduate students enrolled in online learning courses. Quantitative results show that gamified features significantly enhance students’ intrinsic motivation and foster higher participation rates, while qualitative findings reveal that meaningful design and feedback mechanisms contribute to a more positive learning experience. The study highlights that gamification is most effective when aligned with psychological principles such as self-determination, goal orientation, and flow theory. These findings provide important implications for instructional designers and educators in creating engaging digital learning environments that promote sustained motivation and academic achievement.
School-Based Mental Health Interventions: A Systematic Review of Digital CBT Programs for Teens Khan, Omar; Mendes, Clara; Tan, Marcus; Nampira, Ardi Azhar
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 3 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i3.2371

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.
Customer Relationship Management (CRM) Analysis in Customer Retention Haryanto, Rudy; M. Zai, Yovita Yulia; Nampira, Ardi Azhar; Yuliana, Ana; Desembrianita, Eva
Dinasti International Journal of Education Management And Social Science Vol. 6 No. 6 (2025): Dinasti International Journal of Education Management and Social Science (Augus
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v6i6.5461

Abstract

The purpose of this study is to analyze Customer Relationship Management (CRM) in customer retention. This research approach collects data through a literature study, which involves reading literature from various sources including books, reports, articles, and journals through qualitative and deductive approaches. The findings of this study are that Customer Relationship Management (CRM) is an important strategy in increasing customer retention. By utilizing precise segmentation, personalized service, consistent multi-channel interactions, and real-time satisfaction monitoring, CRM helps companies build stronger and more sustainable relationships with customers. Systematic CRM implementation has been proven to increase loyalty, satisfaction, and operational efficiency, as well as reduce marketing costs. Case studies of global companies such as Amazon and Starbucks demonstrate the success of this strategy in encouraging repeat purchases and strengthening emotional bonds with customers. However, CRM implementation also faces challenges such as lack of system integration, poor data quality, internal resistance, limited technical human resource capabilities, and high implementation costs.
The Impact of Meditation on Brain Structure Changes and Cognitive Function in Young Adults Santos, Luis; Reyes, Maria Clara; Malik, Fatima; Iqbal, Kiran; 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.v4i1.811

Abstract

Meditation has gained significant attention for its potential to enhance cognitive function and promote mental well-being. Previous studies have suggested that meditation can lead to structural changes in the brain, particularly in regions associated with attention, memory, and emotional regulation. However, the precise impact of meditation on brain structure and cognitive function in young adults remains underexplored. This study aims to investigate the effect of regular meditation practice on brain structure changes and cognitive function in young adults. A mixed-methods approach was employed, including structural magnetic resonance imaging (MRI) to assess brain changes and cognitive function assessments, such as attention, memory, and executive function tests, conducted before and after a 12-week meditation intervention. The results showed significant increases in gray matter density in areas related to attention and emotional regulation, including the prefrontal cortex and hippocampus. Cognitive testing revealed improvements in attention, working memory, and cognitive flexibility. These findings suggest that meditation can induce structural changes in the brain that enhance cognitive function, particularly in domains critical for academic and personal development. The study concludes that meditation can be an effective practice for promoting cognitive health and supporting brain development in young adults, highlighting its potential as a non-invasive intervention for cognitive enhancement.
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

Abstract

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.
IoT-Based Solar Power Generation System Design for Real-Time Monitoring Arinie, Farida; Sulaiman, Sulaiman; Tahir, Usman; Nurjannah, Nurjannah; Nampira, Ardi Azhar
Journal of Moeslim Research Technik Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v2i1.1932

Abstract

The increasing demand for renewable energy sources has led to the growing adoption of solar power systems. However, efficient monitoring of these systems is essential for optimizing performance and maintenance. Integrating Internet of Things (IoT) technology offers potential solutions for real-time monitoring and management of solar power generation. This research aims to design an IoT-based solar power generation system that enables real-time monitoring of energy production, system performance, and environmental conditions. The goal is to enhance the efficiency and reliability of solar energy systems through advanced data analytics. A prototype system was developed using IoT sensors to collect data on solar panel output, temperature, and weather conditions. The system utilized a microcontroller for data processing and transmission to a cloud platform for real-time visualization and analysis. User-friendly dashboards were created to facilitate monitoring and alert users to potential issues. The findings demonstrated that the IoT-based system effectively monitored solar power generation, providing real-time data on energy output and environmental factors. The system achieved an accuracy of 95% in data reporting, allowing for timely interventions to optimize performance. Users reported improved decision-making capabilities based on the insights gained from the monitoring system.  
Efficiency of Wireless Charging Systems in High-Speed Electric Vehicles Taryana, Taryana; Sothy, Chak; Nampira, Ardi Azhar
Journal of Moeslim Research Technik Vol. 2 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v2i2.1933

Abstract

The increasing adoption of electric vehicles (EVs) necessitates the development of efficient charging solutions. Wireless power transfer (WPT) technology has emerged as a promising method for enhancing the convenience and efficiency of EV charging. Understanding the efficiency of WPT systems in high-speed charging applications is critical for their widespread implementation. This research aims to evaluate the efficiency of wireless charging systems for high-speed electric vehicles. The study investigates various factors affecting energy transfer efficiency, including alignment, distance, and frequency of operation. An experimental setup was created to test a wireless charging system under controlled conditions. Efficiency measurements were taken at different distances and alignments between the transmitter and receiver coils. Data were analyzed to identify optimal operating conditions and performance metrics. The findings indicated that the wireless charging system achieved an overall efficiency of 85% under ideal conditions. Efficiency decreased with increased distance between the coils, with a notable drop at distances exceeding 20 cm. Optimal alignment was found to enhance energy transfer, significantly improving overall system performance. The study demonstrates that wireless charging systems can be efficient for high-speed electric vehicles, with potential for practical applications in urban environments. These findings highlight the importance of optimizing system design and alignment to maximize efficiency.
Development of an Integrated Communication System for 5G-Based Autonomous Vehicles Rahman, Alkautsar; Souza, Felipe; Gomez, Raul; Setiawati, Rahmi; Nampira, Ardi Azhar
Journal of Moeslim Research Technik Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v2i1.1934

Abstract

The rapid advancement of autonomous vehicle technology necessitates robust communication systems to ensure safety, efficiency, and connectivity. The emergence of 5G technology presents opportunities to enhance communication capabilities for autonomous vehicles, enabling real-time data exchange and improved decision-making. This research aims to develop an integrated communication system for autonomous vehicles utilizing 5G technology. The study focuses on evaluating the performance, reliability, and latency of the proposed system in various driving scenarios. An experimental approach was employed, involving the design and implementation of a 5G-based communication framework for autonomous vehicles. Various tests were conducted in controlled environments to assess communication latency, data throughput, and system reliability. Different vehicular scenarios, including urban and highway driving, were simulated to evaluate performance under diverse conditions. The findings indicated that the integrated 5G communication system achieved a latency of less than 10 milliseconds, significantly enhancing real-time data transmission. Data throughput exceeded 1 Gbps, demonstrating the capability to support high-bandwidth applications. The system exhibited robust performance across various driving scenarios, with minimal data loss and high reliability. The research demonstrates the potential of 5G technology in transforming communication systems
Co-Authors . Syamsulbahri Ahmad Syamsudin Akhtar, Shazia Al-Momani, Ammar Apriyanto, Apriyanto Arinie, Farida Arisondha, Edy Arnes Yuli Vandika Baso Intang Sappaile, Baso Intang Chai, Som Chairuddin Costa, Bruna Costa, Tiago Devi, Syahrani Diana Suksesiwaty Lubis Dina Destari Edwin Sugesti Nasution Eva Desembrianita Farah, Rina Fernandez, Carlos Fernandez, Carloz Fujita, Miku Gomez, Raul Harja, Ngiw Aman Idris, Haziq Iqbal, Kiran Irwanto, Miko Mei Iwan Harsono JAROT BUDIASTO Jenheri, Jenheri Judijanto, Loso Justam, Justam Kara, Sevda Kaya, Cemil Khan, Omar Lee, Ava Lek, Siri Lim, Sofia Lima, Rafaela Liu Yang M. Zai, Yovita Yulia Malik, Fatima Manik, Erba Kalo Martinez, Isabel Mayasari, Nanny Mendes, Clara Moktar, Brilian Muhammad Faisal Ninik Sri Rahayu, Ninik Sri Noor, Asmirin Nurjannah Nurjannah Nurul Huda Pangastuti, Nova Pong, Ming Putri, Agustin Andhika Rahman, Alkautsar Ramos, Nathaniel Razak, Faisal Rejeki, Marsudi Endang Sri Restu Auliani Reyes, Maria Clara Rudy Haryanto Saleh, Mohamad Zein Samaduri, Lutpi Santos, Luis Sari, Arum Fandan Sari, Ira Wulan Sato, Haruka setiawati, rahmi Setyowati Subroto Sinaga, Jernita Siti Aisyah Hanim, Siti Aisyah Siti Annisa Wahdiniawati, Siti Annisa Siti Shofiah Sothy, Chak Souza, Felipe Sulaiman Sulaiman Tahir, Usman Tan, Marcus Taryana Taryana, Taryana Taufik Taufik Telma Anis Safitri Urnika Mudhifatul Jannah, Urnika Mudhifatul Vita Lystianingrum Wiwit Xiang, Yang Yuliana, Ana Yusuf Iskandar Zahir, Roya Zaman, Khalil Zhang Li