Henrik Jensen
Henrik Jensen has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
- Achmad Hidayat Dwi Saputra
Bank Negara Indonesia
1 shared publication - Fajriannoor Fanani
University of Semarang
1 shared publication - Fikri Arsla Ramahdan
University of Raharja
1 shared publication - Irma Shantilawati
Ichsan Satya University
1 shared publication - Jihan Zanubiya
University of Raharja
1 shared publication - Mohammad Annas
University Multimedia Nusantara
1 shared publication
Latest Publications
- Open Access
- 3 February 2025
- Published by Pandawan in Blockchain Frontier Technology
- Vol. 4 (2) , 121∼131
Application of IoT and AI Based on ESP32CAM to Support Sustainable Mobility in Smart Cities
Sustainable mobility is a crucial component of smart city development, aiming to create an efficient, ecofriendly, and high quality urban environment. The rapid urbanization and increasing vehicle numbers have led to traffic congestion, high carbon emissions, and inefficient public transportation systems. To address these challenges, integrating Internet of Things (IoT) and Artificial Intelligence (AI) technologies, particularly through the ESP32CAM platform, offers innovative solutions for realtime monitoring, analysis, and management of transportation systems. This study aims to develop an intelligent mobility system that leverages ESP32CAM as the primary device for capturing visual data, including traffic density, vehicle tracking, and parking area occupancy. The collected data is processed using AI algorithms to generate insights, such as traffic pattern predictions and alternative route recommendations. The gap in existing smart mobility solutions lies in their high implementation costs and limited adaptability to developing regions. this study introduces an affordable and flexible system that optimizes transportation efficiency by up to 30%, reducing travel time and carbon emissions while enhancing public transportation management. The results indicate that implementing this system significantly contributes to sustainable urban development by improving mobility, reducing environmental impact, and accelerating the transformation towards smart cities, especially in developing countries where cost-effective solutions are essential.
- 3 February 2025
- Published by Pandawan in Blockchain Frontier Technology
- Vol. 4 (2) , 121∼131
Open AccessApplication of IoT and AI Based on ESP32CAM to Support Sustainable Mobility in Smart Cities
Sustainable mobility is a crucial component of smart city development, aiming to create an efficient, ecofriendly, and high quality urban environment. The rapid urbanization and increasing vehicle numbers have led to traffic congestion, high carbon emissions, and inefficient public transportation systems. To address these challenges, integrating Internet of Things (IoT) and Artificial Intelligence (AI) technologies, particularly through the ESP32CAM platform, offers innovative solutions for realtime monitoring, analysis, and management of transportation systems. This study aims to develop an intelligent mobility system that leverages ESP32CAM as the primary device for capturing visual data, including traffic density, vehicle tracking, and parking area occupancy. The collected data is processed using AI algorithms to generate insights, such as traffic pattern predictions and alternative route recommendations. The gap in existing smart mobility solutions lies in their high implementation costs and limited adaptability to developing regions. this study introduces an affordable and flexible system that optimizes transportation efficiency by up to 30%, reducing travel time and carbon emissions while enhancing public transportation management. The results indicate that implementing this system significantly contributes to sustainable urban development by improving mobility, reducing environmental impact, and accelerating the transformation towards smart cities, especially in developing countries where cost-effective solutions are essential.
- Open Access
- 29 January 2025
- Published by iLearning Journal Center in Aptisi Transactions on Management (ATM)
- Vol. 9 (1) , 82-91
Assessing the Influence of Green Supply Chain Initiatives on Corporate Performance Using SmartPLS
This study investigates the influence of Green Supply Chain Initiatives (GSCI) on Corporate Performance (CP), emphasizing the mediating role of Operational Efficiency (OE). Using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS, the research analyzes survey data collected from SESINDO organizations. GSCI, encompassing practices such as green procurement, eco-design, and waste management, are examined for their impact on financial, operational, and environmental performance. The findings reveal a significant positive relationship between GSCI and CP, highlighting that sustainable practices enhance financial outcomes, operational efficiencies, and environmental impact reduction. Furthermore, OE is identified as a partial mediator, amplifying the benefits of GSCI on CP. This underscores the importance of optimizing resource utilization and streamlining processes to maximize the impact of sustainability initiatives. The study contributes to theory by integrating the Resource-Based View (RBV) and Institutional Theory, offering a comprehensive understanding of GSCI adoption and outcomes. Practically, it provides actionable insights for business leaders and policymakers to promote sustainability while achieving competitive advantage. Despite its contributions, the study acknowledges limitations, such as its cross-sectional design and regional focus, and suggests future research in diverse contexts. This research underscores the transformative potential of GSCI in driving sustainable corporate success.
- 29 January 2025
- Published by iLearning Journal Center in Aptisi Transactions on Management (ATM)
- Vol. 9 (1) , 82-91
Open AccessAssessing the Influence of Green Supply Chain Initiatives on Corporate Performance Using SmartPLS
This study investigates the influence of Green Supply Chain Initiatives (GSCI) on Corporate Performance (CP), emphasizing the mediating role of Operational Efficiency (OE). Using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS, the research analyzes survey data collected from SESINDO organizations. GSCI, encompassing practices such as green procurement, eco-design, and waste management, are examined for their impact on financial, operational, and environmental performance. The findings reveal a significant positive relationship between GSCI and CP, highlighting that sustainable practices enhance financial outcomes, operational efficiencies, and environmental impact reduction. Furthermore, OE is identified as a partial mediator, amplifying the benefits of GSCI on CP. This underscores the importance of optimizing resource utilization and streamlining processes to maximize the impact of sustainability initiatives. The study contributes to theory by integrating the Resource-Based View (RBV) and Institutional Theory, offering a comprehensive understanding of GSCI adoption and outcomes. Practically, it provides actionable insights for business leaders and policymakers to promote sustainability while achieving competitive advantage. Despite its contributions, the study acknowledges limitations, such as its cross-sectional design and regional focus, and suggests future research in diverse contexts. This research underscores the transformative potential of GSCI in driving sustainable corporate success.
- Open Access
- 2 October 2024
- Published by Pandawan in International Journal of Cyber and IT Service Management
- Vol. 4 (2) , 88-96
Challenges in Securing Data and Networks from Modern Cyber Threats
In the era of digital transformation, organizations face an increasing array of cyber threats that target data and network security. This study focuses on the key challenges encountered in protecting sensitive information and network infrastructures from evolving cyberattacks, such as ransomware, phishing, and advanced persistent threats. The objective is to explore the current landscape of cyber threats and identify the major hurdles in implementing effective security measures. Through a mixed-method approach involving surveys and case studies, the research highlights the skills gap, complexity of network architectures, and the rapid advancement of threats as primary obstacles. The findings underscore the need for advanced security solutions, such as AI-driven threat detection and zero trust models, to enhance organizational resilience. Addressing these challenges is critical to safeguarding data, ensuring business continuity, and maintaining regulatory compliance.
- 2 October 2024
- Published by Pandawan in International Journal of Cyber and IT Service Management
- Vol. 4 (2) , 88-96
Open AccessChallenges in Securing Data and Networks from Modern Cyber Threats
In the era of digital transformation, organizations face an increasing array of cyber threats that target data and network security. This study focuses on the key challenges encountered in protecting sensitive information and network infrastructures from evolving cyberattacks, such as ransomware, phishing, and advanced persistent threats. The objective is to explore the current landscape of cyber threats and identify the major hurdles in implementing effective security measures. Through a mixed-method approach involving surveys and case studies, the research highlights the skills gap, complexity of network architectures, and the rapid advancement of threats as primary obstacles. The findings underscore the need for advanced security solutions, such as AI-driven threat detection and zero trust models, to enhance organizational resilience. Addressing these challenges is critical to safeguarding data, ensuring business continuity, and maintaining regulatory compliance.