Mercu Buana University

Southeast Asian countries, as members of the Association of Southeast Asian Nations (ASEAN), hold the second-largest Sharia financial assets globally. This study aims to assess the comparative performance of Islamic banks across ASEAN, examine the relationship between Islamic conformity, profitability, and green banking practices, and compare performance indicators between Malaysian and Indonesian Islamic banks. The sample includes Islamic banks from Indonesia, Malaysia, Brunei Darussalam, Thailand, and the Philippines. The findings reveal consistent adherence to Sharia principles across all banks, demonstrating strong Islamic conformity. However, financial performance indicators such as Return on Assets (ROA), Return on Equity (ROE), and Net Profit Margin (NPM) show significant variability, reflecting differences in operational efficiency and profitability. Green banking practices positively correlate with profitability, particularly ROA and NPM, emphasizing the role of Environmental, Social, and Governance (ESG) initiatives in enhancing operational efficiency and customer loyalty. The comparative analysis highlights that while both Malaysian and Indonesian Islamic banks exhibit consistent Islamic conformity, Malaysian banks outperform their Indonesian counterparts in green banking practices and profitability. This advantage is attributed to Malaysia’s advanced regulatory environment, which promotes sustainable finance, whereas Indonesian banks face greater profitability variability, necessitating improved governance and operational strategies. These findings offer valuable insights for policymakers and stakeholders, showcasing how Islamic financial principles can integrate with sustainability practices to achieve profitability and environmental responsibility in Islamic banking. Acknowledgment(s)The authors extend their gratitude to the Ministry of Higher Education, Science and Technology of the Republic of Indonesia for funding this research and to the Research and Community Service Centre of Universitas Mercu Buana for their valuable support.

Subject and purpose of work This study aims to analyze the relationship between the variables of security, information quality, ease of use perceived usefulness, and perceived trust toward intention to use online food delivery applications. The study involved 218 micro and small industry entrepreneurs in the culinary field. Materials and methods Researchers used SEM-PLS (Partial Least Square) as a technique used to analyze measurements and structural models. Results This study shows that the variables of security, ease of use, and perceived usefulness have a significant positive effect on intention to use food delivery applications. Conclusions Theoretical and practical implications, researchers need to test the variable of interest in using other variables and food delivery application providers need to pay attention to the behavior and characteristics of micro and small industry entrepreneurs to apply for food delivery applications in improving their business.

Blockchain technologies have recently garnered substantial attention in research and industry sectors due to their potential advantages across various industries. Blockchain provides an effective solution to address challenges by offering distributed, secure, and permissioned transactional ledgers. This paper introduces an innovative conceptual framework that integrates blockchain technology with building information modeling, specifically designed for digital transactions and smart contracts in the retrofitting of green buildings within the chemical industry. The core objectives include enhancing cost efficiency, fortifying cyberse-curity measures, improving information management and sharing, simplifying payment transactions , and promoting sustainability in this specific context. The research, conducted at a chemical facility in Cilegon, Banten, Indonesia, utilizes Structural Equation Modeling-Partial Least Squares (SEM-PLS) to analyze questionnaire data and identify influential factors. Results indicate that incorporating Blockchain-BIM leads to cost savings of 4.42%, 4.45%, and 4.40% for low-level, medium-level, and high-level retrofitting categories, respectively, highlighting the significant role of Blockchain-BIM in enhancing cost efficiency throughout the retrofitting process. ARTICLE HISTORY

The combination of Generative AI and IoT technologies has created opportunities to improve the capabilities and efficiency of Healthcare Systems. This integration has the capacity to transform several sectors, such as healthcare, manufacturing, transportation, and smart cities. Generative AI systems give machines with tangible existence and independent decision-making powers, while IoT enables effortless connection and data interchange between physical objects and digital systems. This research examines the difficulties and potential advantages of incorporating Generative artificial intelligence systems into internet of things-based Healthcare systems. The study first examines the structure and elements of Generative AI systems and IoT-based Healthcare Systems, emphasizing their individual functions and interconnections. Subsequently, it analyzes the advantages of integrating various technologies, including improved perception of the surrounding circumstances, immediate and informed decision-making, and flexible responses in ever-changing settings. Furthermore, the study discusses the difficulties linked to this integration, including interoperability, security, privacy, and ethical issues. In addition, the paper showcases several instances and uses where the combination of Generative AI systems with IoT-based Healthcare Systems has shown notable progress. These include self-governing robotic systems in advanced manufacturing, intelligent gadgets for healthcare monitoring, self-driving automobiles, and systems for managing smart infrastructure. In addition, the study explores forthcoming areas of research and upcoming developments in this domain, including edge computing, swarm robotics, human–robot cooperation, and decentralized AI. Furthermore, it underscores the need of multidisciplinary cooperation among specialists in AI, IoT, robotics, cybersecurity, and domain-specific businesses to tackle intricate obstacles and fully unlock the potential of integrated Generative AI systems in IoT-based Healthcare Systems. Ultimately, the incorporation of Generative AI systems into IoT-based Healthcare Systems shows great potential for developing highly intelligent, adaptable, and effective Healthcare systems in several fields. Nevertheless, it necessitates meticulous examination of technological, ethical, and sociological ramifications to guarantee responsible implementation and optimize the advantages for mankind.

This study aims to explore the influence of risk management and digital technology literacy on learning innovation performance, with a particular focus on the moderating role of modern learning environments. The research employs a quantitative approach using data collected from 385 Indonesian university students, analyzed through Structural Equation Modeling-Partial Least Squares (SEM-PLS) to validate the proposed framework. The results demonstrate that effective risk management significantly enhances institutional adaptability and fosters success in implementing innovative learning strategies. Moreover, higher levels of digital technology literacy empower students to engage more effectively with modern learning technologies, leading to improved performance outcomes. The findings also highlight that the moderating effect of modern learning environments strengthens these relationships, underscoring the importance of robust digital infrastructure and adaptive pedagogy. This study provides theoretical contributions by integrating risk management, digital literacy, and innovation within the context of education. Practical implications include recommendations to optimize risk management frameworks, enhance digital literacy programs, and invest in modern learning ecosystems to support academic success and institutional resilience.

The increasingly widespread use of composite materials for structural materials forces composite materials to have superior mechanical properties, one of which is impact strength. The material’s impact strength was determined by calculating the impact energy obtained from the impact test. Many things impact the strength of composite materials. Many studies have been conducted on the mechanical properties of composite materials. However, the above research has not investigated the influence of the morphology of the second phase on the mechanical properties of resin composite materials. The morphology of the second phase used as reinforcement in composite materials can be particles, short fibers, or continuous fibers. The shape (morphology) of the second phase affects the impact strength of the composite material. Therefore, this study was intended to examine the effect of the morphology of Coir Coconut fiber as the second phase (reinforcement) combined with the percentage of its content in epoxy resin matrix composite on the impact strength, as well as to determine the optimum morphology and the percentage of the second phase. The study was designed using the full factorial. Furthermore, the data on the impact strength of the specimens were analyzed to obtain a regression model for the relationship between the morphology of the second phase and the percentage of the content of the second phase on the impact strength. With this regression model, it is possible to predict the impact strength of various morphological forms of the second phase and optimize the optimum content of the second phase.

Humans need fresh and clean air to live healthily. However, being in a dense and dense residential environment can potentially transmit diseases such as infections, bacteria, viruses, airborne microorganisms (airborne microorganisms), fungi, and other sources of infectious diseases. This is a concern in the air conditioning system. The air conditioning system regulates the air conditioning in the room to meet ideal conditions such as temperature and humidity. If you look at the Technical Guidelines for Buildings and Infrastructure Standards for Emerging Infectious Diseases (PIE) Isolation Rooms from the Ministry of Health of the Republic of Indonesia in 2020, at least the air temperature of residential rooms can reach an air temperature of 24 ± 20°C, with a relative humidity of 60%, so that fresh air is fulfilled. Experiments on portable humidifiers using single and double condensers from a refrigeration system provide design data on the need for air temperature and humidity for isolation rooms in simple residential houses. The standard temperature can be reached in a portable humidifier with a single condenser, namely 26-28°C. However, the humidity is still relatively high, at 80%, so bacteria can survive. However, when the air temperature in the lowest section (evaporator) is conditioned (10, 15, and 20°C), the air temperature exceeds the standard limit (39,38°C), even though the humidity is very low, reaching 34%. In experiments using a double condenser, the standard temperature and humidity can be said to be achieved; the temperature is 31°C, and the humidity is at 67%.

The existence of public spaces dates back to Ancient Roman, Greek, and the present day. Although people today are known for their individualistic attitudes, they still need a place to communicate. However, public space is present everywhere possible, one of which is currently in place owned by the private sector. The presence of public spaces by the user is significant because, without users, public spaces would not “live.” The presence of visitors in a public place may be due to the visitor’s need for an activity in that place or the absence of a necessity. This study uses quantitative research to discuss visitors’ attachment to public open spaces. Research results show visitors attach to different affective and functional relationships with public spaces. Visitors’ functional links to public spaces are superior to emotional connections. Overall, this study shows visitors feel engaged with the public search space. Some things don’t make visitors feel connected regarding their internal relationship to the public space. This research is helpful for designers of public spaces in private spaces to realize designs that are appealing to their visitors. This research can contribute to creating more inclusive, resilient, and sustainable urban environments, aligning with the SDGs 11, 3, 8, and 9.

In Tangerang Indonesia, the Citra Raya residential area, three Citra Raya Conservation Lakes function as sources of clean water production. The area is flooded when the lake overflows during the rainy season. Community access to clean water is disrupted throughout the dry season due to a decrease in clean water discharge. So an effort is needed to increase the sustainability of its availability in achieving sustainable development goals (SDGs). This research was conducted to determine the water balance and improve water management in the three lakes. The water demand study was carried out based on the number of active consumers in 2020 and predictions until 2025. Flow characteristics and a basic planning-month approach were used to analyze water availability. Water balance analysis is used to compare the availability of reliable discharge and its needs as a basis for optimization. Optimization using linear programming. Optimization results show that the availability of raw water in the conservation lake is sufficient to meet the clean water demand of the Citra Raya area every month. However, in reality, there are problems such as pipe leaks and legal violations. This requires further research.

This study analyzes the wind characteristics and energy potential at two locations in Indonesia, Haharu and Laepori, on the northern coast of Sumba, over ten years (2011-2020). The data were obtained from NASA’s Langley Research Center (LaRC) POWER Project and processed using windographer software. The analysis covers various aspects such as wind speed, wind direction, Weibull distribution parameters, wind power density (WPD), and the net energy output of a horizontal wind turbine. The results show that both locations have similar wind patterns and performance, with minor differences in certain months and years. Haharu generally has a higher average wind speed, wind power density, and net energy output than Laepori. The dry season (May to August) is the most favorable period for wind energy production at both locations, while November, December, and March are the least favorable. The prevailing wind direction is southeast for both locations. The study employs an 800 kW Enercon E-48/800 kW turbine to evaluate the potential electrical energy output. The results show that Haharu outperforms Laepori’s net mean power output, with Haharu producing 106.8 kW compared to Laepori’s 103.8 kW.

In most of Indonesia, floods are a common natural disaster that spreads into several watersheds during the rainy season. When river water outflow increases to the point where it overflows and floods the surrounding area, this is known as a flood. Over the past few years, there has been an increasing number of flood incidents throughout the rainy season, which has resulted in significant losses for those impacted by this calamity. One of the rivers in Bali’s Jembrana district is Tukad Biluk Poh. It has a watershed area of around 84 km2, is about 28 km long, flows into the Indian Ocean, and is one of the rivers that floods the most. Access to Gilimanuk to Denpasar via the national road was not immune to the flood overflow at the time in Tukad Biluk Poh. To prevent flooding on this portion of the road, this study aimed to ascertain the flood water level on the Gilimanuk-Denpasar National Road bridge that crosses Tukad Biluk Poh. When the flood discharge was analyzed using the Nakayasu method’s synthetic unit hydrograph, the design flood discharge had return periods of 299,720 m/sec for two years, 436,764 m3/sec for five years, 529,525 m3/sec for ten years, 648,435 m3/sec for twenty-five years, and 1134,737 for a thousand years. The HEC-RAS tool was then used for a hydraulic analysis to ascertain the flood water level, and the findings were excellent. For two years, MAB yields 1.78m, for five years, 2.31m; for ten years, 2.64m; and twenty-five years, 2.64m. 3.03 years, with MAB returning 3.34 years, 1 MAB returning 3.51 years, MAB returning 5.76 years, and MAB returning 6.21 years. The bridge is referred to as the current one by obtaining the flood water level at the 200th year return period of the bridge’s condition, which is 4.65 meters on the pavement and 3.10 meters on the bottom of the girder at the design flood water level. Based on the analysis, the bridge’s height was raised to 7.71 meters at the base of the top structure, considering a 1000-year design flood and a 1.50-meter guard height.

This paper proposes a single-port interdigital capacitor (IDC) resonator based on asymmetric branch feed line with high stability performance for permittivity detection of solid materials with a permittivity range of 1 - 6.15. The microwave sensor is designed using a single-port resonator operating at two different resonant frequencies f_r1 = 1.61 GHz and f_r2 = 2.52 GHz. Dual band frequency was proposed using asymmetric branch feed line. In addition, to confine the electric field concentration of the resonator, an interdigital capacitor (IDC) structure is proposed as a solution. Furthermore, a copper shield was proposed as conducting material to evaluate performance stability of the sensor from disturbance effect with range of d = 1 cm – 2.5 cm. Based on the measurement results, the sensor has high stability both without and with disturbance with an a Frequency Detection Resolution (FDR) of 0.009 - 0.4 GHz/Δε_r, a Normalized Sensitivity (NS) of 0.4% - 4.4%, and an average accuracy of 90% - 95% for both resonance frequencies, respectively. Therefore, this sensor can be recommended for several applications such as biomedical industry, pharmaceuticals and material quality control especially for outdoor measurements that are potentially affected by electromagnetic interference and disturbance.

Gait recognition is a remote biometric technology that utilizes the dynamic characteristics of human movement to identify individuals even under various extreme lighting conditions. Due to the limitation in spatial perception capability inherent in 2D gait representations, LiDAR can directly capture 3D gait features and represent them as point clouds, reducing environmental and lighting interference in recognition while significantly advancing privacy protection. For complex 3D representations, shallow networks fail to achieve accurate recognition, making vision Transformers the foremost prevalent method. However, the prevalence of dumb patches has limited the widespread use of Transformer architecture in gait recognition. This paper proposes a method named HorGait, which utilizes a hybrid model with a Transformer architecture for gait recognition on the planar projection of 3D point clouds from LiDAR. Specifically, it employs a hybrid model structure called LHM Block to achieve input adaptation, long-range, and high-order spatial interaction of the Transformer architecture. Additionally, it uses large convolutional kernel CNNs to segment the input representation, replacing attention windows to reduce dumb patches. Extensive experiments demonstrated that HorGait achieved a Rank-1 accuracy of 82.54% on the SUSTech1K dataset, surpassing the state-of-the-art Transformer architecture method by 8.33%. This confirms the hybrid model’s ability to execute the complete Transformer process and excel in point cloud planar projection. The outstanding performance of HorGait offers new insights for the future application of the Transformer architecture in gait recognition.

Environmental, social, and governance (ESG) performance is critical in mitigating climate change. Energy companies must include ESG practices in their business plans because they can determine firm value. This study investigates the impact of ESG and firm size on firm value in Indonesian energy sector, which is moderated by profitability through return on assets. This study uses a sample of 19 energy companies listed on the Indonesia Stock Exchange from 2016 to 2022. A panel data regression model is applied to estimate the impact of ESG practices and firm size on firm value with the moderating role of return on assets. The study results found that ecological, social, and governance disclosure in the model with return on assets as a moderator independently positively impacts firm value but not vice versa. The interaction between return on assets and ESG practices has no impact on firm value, which means that the role of return on assets as a moderator cannot strengthen the influence of ESG and firm size on firm value. Return on assets positively impacts firm value if it acts as an independent variable without a moderator. Firm size independently has a negative impact on firm value but has no effect if it interacts with return on assets. The implications of the empirical findings provide recommendations for policymakers, corporate management, investors, and academics. Environmental, social, and governance disclosure practices are essential to pay attention to as they can improve sustainability performance and firm value in the energy sector of Indonesia. AcknowledgmentAcknowledgments are expressed to the Directorate General of Higher Education, Research, and Technology, Ministry of Education, Culture, Research and Technology for the Funding Assistance for the Master’s Thesis Research Grant Scheme [Contract Number: 01-1-4/675/SPK/VII/2024].

This study aims to provide an empirical analysis of publications in employee green behavior based on journal articles by revealing publication trends, impactful authors, leading journals, and the most influential articles. It also explores the knowledge structures including social, intellectual, and conceptual structure. This study used bibliometric and content analyses to analyze 429 journal articles on employee green behavior indexed by Scopus or Web of Science published between 1993 and March 2024. The results revealed increased interest and activity in studying employee green behavior over the past decade. The research has identified key bibliometric elements, namely impactful authors, leading journals, and the most influential articles. Further, this study has also described the knowledge structures including conceptual, intellectual, and social structure. We identified three clusters of research in the existing literature. The first cluster explores the role of organizational factors, the second examines the role of employee personal factors, and the third specifically focuses on the role of Green Human Resource Management (GHRM) practices. This study highlights the need for longitudinal studies to assess employee green behavior change over time, as well as which factors are most important among those previously identified. Comparative studies are also needed to understand the employee green behavior differences accross different cultural and organizational contexts.

Rapid technological advances have made financial markets more accessible and encouraged individual investors to engage in investment decision-making actively. Generation Z, or Gen Z, characterized by higher levels of digital literacy, a high sense of curiosity, and acceptance of innovation, tends to make investment decisions quickly. This study aimed to analyze the effect of technological progress, financial literacy, and financial attitudes on investors’ investment decisions. There are 125 Gen Z investors in Jakarta, Indonesia, selected as research samples using the non-probability sampling method. The survey method was employed to collect data, and the study instrument was a questionnaire. For data analysis, Partial Least Squares version 4.0 was used. The study’s findings revealed that financial literacy and financial attitude positively influence Gen Z investment decisions. Technological progress does not affect Gen Z in determining investment in the financial market. Financial literacy and financial attitude are more dominant for Gen Z investors than technological progress in determining investment allocation. This finding implies that Gen Z must improve their understanding of correct financial literacy and financial attitudes that align with individual investors’ character. Further investigation needs to reveal the insignificance of technological progress in determining investment decisions. Technological progress and financial literacy likely have the same factor characteristics related to three dimensions: knowledge, skills, and attitudes. The attitude of Gen Z investors towards the progress of financial technology by investors is preceded by good financial literacy. Therefore, it is necessary to test the relationship between variables, both mediation and moderation, in investment decisions.

Trains are a popular mode of transportation in Indonesia. People from higher and lower socioeconomic brackets are increasing interest in the industry as it gets more well-known. Some safety equipment is available, but mishaps can still occur. People attempting to determine where a problem originated often use such as the Ishikawa model for assistance. The Poisson model is well-suited for crash simulation, and this work provides a valuable method for doing so. A root cause analysis allows for identifying and eliminating the accident’s most significant contributing factors. From 1999 to 2014, data was gathered through a variety of intermediaries. According to Ishikawa’s research, ten primary factors influence the frequency of accidents. There are issues with the route, the train, the signals, the upkeep, the communication, the processes, the personnel, the climate, and the machinery. Next, we use the Dispersion and Vuong tests to see which of the regression models provides the most accurate forecasts. Using the Vuong test, the Zero-inflated model has the best predictive power for accidents and events, with p-values of 0.19695481, 0.1301056, and 0.0689108. Train derailments, collisions, and SPAD are the most common causes of accidents.

As a novel eco-friendly material, geopolymer boasts impressive sustainability, technical performance, and commercial prospects. In addition, geopolymer offers significant benefits for soft soil foundation reinforcement. This chapter focuses on the challenges and progresses of geopolymer technology as a viable strategy for soft soils stabilization, and examines the potential and constraints of geopolymer as an alternative to traditional cement.

This study explores the impact of adoption of digital banking, digital payment volume, and customer awareness of green banking features on environmental sustainability, focusing on carbon footprint reduction in Asia. The findings indicate that digital banking is crucial in minimizing paper usage and reducing energy consumption, significantly lowering the carbon emissions associated with traditional banking operations. The research employs Structural Equation Modeling (SEM) to analyze data from 520 respondents, providing a comprehensive view of the direct and indirect relationships between digital banking practices and environmental outcomes. The results demonstrate that increased digital payment volume, combined with higher customer awareness of sustainability, reduces the reliance on paper-based banking and helps achieve broader environmental goals. The study highlights the mediating role of paper usage in lowering carbon footprints and underscores the importance of digital transformation and customer education in driving sustainable banking practices. This research contributes valuable insights for policymakers and financial institutions aiming to integrate fintech with sustainability initiatives.