Politeknik Negeri Bandung

We report the preparation of the free-standing magnetic film using solution casting method with κ-carrageenan as the matrix and magnetite nanoparticles (Fe 3 O 4 NP) as the magnetic material. The obtained film has a black-brown color and good responsiveness when exposed to permanent magnet. Fe 3 O 4 NP are evenly distributed over the κ-carrageenan matrix and tend to form agglomerations when the number of nanoparticles is increased. The presence of Fe 3 O 4 NP capped by trisodium citrate was demonstrated by the FTIR results of Fe-O, symmetric carboxylate (-COO-), and antisymmetric carboxylate stretching vibrations, respectively at wavenumbers of 418.6 cm ⁻¹ , 1458.2 cm ⁻¹ , and 1654.9 cm ⁻¹ . Functional groups in κ-carrageenan also appeared indicating that Fe 3 O 4 NP attached to-carrageenan matrix. The M-H curve of the magnetic film shows the increase in Fe 3 O 4 NP content would increase the magnetization value. The small coercivity field of the magnetic film value shows that the magnetic film is a soft ferromagnetic material.

Heating, Ventilation, and Air Conditioning (HVAC) systems are critical for maintaining thermal comfort in office environments which also crucial for occupant well-being and productivity. This study investigates the impact of integrating ceiling fans with higher air conditioning setpoints on thermal comfort and energy efficiency in office environments. Field measurements and questionnaire surveys were conducted to evaluate thermal comfort and energy-saving potential under varying conditions. Results show that increasing the AC setpoint from 25°C to 27°C, combined with ceiling fan operation, reduced power consumption by 10%, achieving significant energy savings. Survey data confirmed that 85% of participants reported consistent thermal sensations across all conditions, with ceiling fans effectively compensating for higher setpoints through enhanced air circulation. CFD simulations revealed that medium-speed ceiling fan operation produced the most uniform airflow distribution, with an average air velocity of 0.45 m/s, and minimized temperature variations, ensuring balanced thermal conditions. Temperature analysis showed a reduction in hotspots and cold zones, maintaining an average temperature deviation of less than ±0.5°C. Predicted Mean Vote (PMV) evaluations at a 27°C setpoint indicated improved thermal comfort, with average PMV values around −0.3, corresponding to a “neutral” thermal sensation. These findings demonstrate the effectiveness of integrating ceiling fans with HVAC systems in achieving energy efficiency and occupant comfort, offering a sustainable approach to reducing AC energy consumption in office environments.

Background and Aims The increasing elderly population presents significant challenges for healthcare systems, necessitating innovative solutions for continuous health monitoring. This study develops and validates an IoT‐based elderly monitoring system designed to enhance the quality of life for elderly people. The system features a robust Android‐based user interface integrated with the Firebase cloud platform, ensuring real‐time data collection and analysis. In addition, a supervised machine learning technology is implemented to conduct prediction task of the observed user whether in “stable” or “not stable” condition based on real‐time parameter. Methods The system architecture adopts the IoT layer including physical layer, network layer, and application layer. Device validation is conducted by involving six participants to measure the real‐time data of heart‐rate, oxygen saturation, and body temperature, then analysed by mean average percentage error (MAPE) to define error rate. A comparative experiment is conducted to define the optimal supervised machine learning model to be deployed into the system by analysing evaluation metrics. Meanwhile, the user satisfaction aspect evaluated by the terms of usability, comfort, security, and effectiveness. Results IoT‐based elderly health monitoring system has been constructed with a MAPE of 0.90% across the parameters: heart‐rate (1.68%), oxygen saturation (0.57%), and body temperature (0.44%). In machine learning experiment indicates XGBoost model has the optimal performance based on the evaluation metrics of accuracy and F1 score which generates 0.973 and 0.970, respectively. In user satisfaction aspect based on usability, comfort, security, and effectiveness achieving a high rating of 86.55%. Conclusion This system offers practical applications for both elderly users and caregivers, enabling real‐time monitoring of health conditions. Future enhancements may include integration with artificial intelligence technologies such as machine learning and deep learning to predict health conditions from data patterns, further improving the system's capabilities and effectiveness in elderly care.

Literature indicates that environmental performance has received special attention due to the increasing awareness of business managers on its positive impacts on the economy, society and environment. However, few studies have been conducted to examine the drivers of green innovation i.e. green human resource management, environmental strategy, environmental legitimacy towards environmental performance in the context of hospitality industry especially in developing countries. This study aims to examine the relationship between green human resource management, environmental strategy, environmental legitimacy, green innovation, and environmental performance in the hospitality industry both in direct and mediation relationships. Data were collected from hotel and restaurant managers in Bali, Indonesia. Smart-PLS was used to examine the validity and reliability of the proposed structural equation modeling. The findings of the present study revealed that green human resource management significantly influences environmental strategy, legitimacy, green innovation and environmental performance. Furthermore, environmental strategy, legitimacy, and green innovation mediate the relationship between GHRM and environmental performance. This study contributes to theoretical and practical implications and provides valuable suggestions, especially for managers in the hospitality industry for environmental conservation.

In addition to being used as a fuel and propellant, dimethyl ether (RE170) can also be used as an environmentally friendly refrigerant. Apart from having zero ozone depletion potential (ODP), this compound also has a very low global warming potential (GWP), making it safe for the environment. This study aims to compare the performance of refrigeration machines using RE170 and R410, which has long been used as a refrigerant in air conditioning systems. The study was conducted at various evaporation and condensation temperatures. The results showed that RE170 does have a lower cooling capacity, about 41.5% of the cooling capacity of R410A. However, the power required on the system with RE170 is very low, which is only about 35.5% compared to the power required by the system with R410. As a result, the system with RE170 has 16.9% better energy efficiency. Thus, RE170 is not only environmentally friendly but also energy efficient. Another important finding of this study is that RE170 is superior to R410A in terms of energy efficiency at high condensing temperature.

Dimethyl ether is an organic compound that has the potential to be used as an environmentally friendly refrigerant. In this study, the performance of dimethyl ether refrigerant was tested and compared with other refrigerants having high working pressure, namely R410A, R410B, and R32. The study results show that dimethyl ether has a lower cooling capacity compared to R410A, R410B, and R32, in the order of 37% to 40%. However, the compression work of the cooling system with dimethyl ether is much lower, i.e., in the order of 30.7% to 36.9%. As a result, the coefficient of performance (COP) of the cooling machine with dimethyl ether is 7.4% to 10.6% higher than that of the three high-pressure refrigerants. The COP increases with the increase of evaporating temperature.

The global shift towards digitalizing government organizations reflects citizens’ growing reliance on technology. This study explores the impact of strategic resources like data literacy, collaborative skills, and digital trust in government H.R. on digital culture, readiness, and overall digitalization. Despite numerous studies on digitalization in government organizations, limited attention has been given to the role of human resource (H.R.) strategic factors in shaping digital culture and readiness. Analyzing data from 257 government employees using SEM-PLS, the research highlights the crucial roles of data literacy and digital trust in shaping organizational digital culture. Moreover, it finds that digital culture and readiness significantly affect digitalization efforts. These findings not only enhance our understanding of digitalization in government but also validate existing technology adoption theories. The study offers a practical framework for evaluating digitalization performance, aiding policymakers and leaders in navigating digital transformation complexities. It stresses the importance of investing in human capital and fostering a supportive digital environment. Ultimately, such efforts are crucial for governments to effectively utilize digital technologies, improve service delivery, and address citizens’ evolving needs in an increasingly digital world.

Vehicular Ad-Hoc Networks (VANETs) play an essential role in the intelligent transportation era, furnishing users with essential roadway data to facilitate optimal route selection and mitigate the risk of accidents. However, the network exposure makes VANETs susceptible to cyber threats, making authentication crucial for ensuring security and integrity. Therefore, joining entity verification is essential to ensure the integrity and security of communication in VANETs. However, to authenticate the entities, authentication time should be minimized to guarantee fast and secure authentication procedures. We propose an authentication system for VANETs using blockchain and Kerberos for storing authentication messages in a blockchain ledger accessible to Trusted Authentication Servers (TASs) and Roadside Units (RSUs). We evaluate the system in three diverse network scenarios: suburban, urban with 1 TAS, and urban with 2 TASs. The findings reveal that this proposal is applicable in diverse network scenarios to fulfill the network requirements, including authentication, handover, and end-to-end delay, considering an additional TAS for an increasing number of vehicles. The system is also practicable in storing the authentication message in blockchain considering the gas values and memory size for all scenarios.

Environmental conditions are becoming increasingly critical due to the high volume of waste, with households contributing 61% of the total. The complexity of the waste issue poses significant challenges to achieving the Sustainable Development Goals (SDGs). This study intends to predict household waste-related behavior by proposing a novel approach that integrates the Theory of Planned Behavior (TPB) with responsible consumption. Data were gathered from 404 Indonesian households using a Likert scale questionnaire and analyzed using Structural Equation Modeling (SEM)-AMOS to assess the structural model. The results reveal that attitudes, perceived behavioral control, intention to sort waste, and responsible consumption significantly influence household waste behavior. Additionally, responsible consumption does not significantly moderate the effect of perceived behavioral control on waste sorting engagement but does significantly enhance the development of waste sorting behaviors. This study is unique in its integration of TPB with responsible consumption to predict waste behavior, particularly within the context of Indonesia, where demographic and psychographic factors contribute to high levels of waste generation.

Adolescents are a productive age group that will play an important role in achieving the demographic bonus in Indonesia by 2030. Problems that can be encountered in adolescents include knowledge, attitudes and sexual behaviour related to reproductive health. Their sexual behaviour can reflect their understanding as adolescents regarding their level of future readiness (e.g., long, healthy, happy, prosperous life). This research aims to analyse the relationship between family roles, sexual behaviour and the level of future readiness among adolescents in Indonesia. This research uses secondary data from the 2019 Program Performance and Accountability Survey results from the National Population and Family Planning Agency, the Central Statistics Agency, and universities in 34 provinces in Indonesia. The sample was young men and women aged 10–24 who were unmarried for the last six months and were registered as family members in selected households in Indonesia. Data were analysed using descriptive, bivariate and multivariate analysis with logistic regression. The result showed that the individual factors associated with adolescents' level of future readiness are age group (0.000), gender (0.018), education (0.000), and adolescent reproductive health (ARH) knowledge (0.000). Family factors associated with adolescents' level of future readiness are parental exposure to ARH (0.000) and implementation of family roles (0.000). The environmental factors associated with adolescents' level of future readiness are the source of ARH information through mass media (0.000) and the source of population information through mass media (0.000). Implementing family roles is the most dominant factor influencing adolescents' level of future readiness.

The digital divide makes it difficult for companies to find workers with digital skills. Usually occurs in developing countries, including Indonesia. Therefore, analyzing and investigating digital human resource behavior and performance is necessary. This research aims to investigate and analyze digital behavior and employee performance. The study used an explanatory survey method, carried out from March 2023 - May 2023, at a state company owned by the Indonesian government. The total sample is 149 employees. Data collection uses a questionnaire converted into G-form and distributed with the help of social media. The questionnaire was tested for validity and reliability. Data analysis uses descriptive analysis, factor analysis, and multiple regression. The research results found three dimensions/sub-variables of digital behavior, and we named them digital knowledge & skills, availability of digital technology, and adoption of digital technology innovation. These three dimensions positively impact employee performance, especially the performance of employees belonging to Generation Z. This research also proves that digital behavior in the workplace can be developed if there is support from leadership, availability of technology, and increasing adoption by learning from each other among employees. In the future, this research needs to be continued from the perspective of leaders and consumers.

Implementing and communicating Corporate Social Responsibility (CSR) is the primary foundation for businesses to accomplish the Sustainable Development Goals. In this perspective, mining operations are seen as one of the most harmful corporate activities when compared to other businesses that utilize natural resources; therefore, these companies must strongly implement and demonstrate higher CSR. The Feasible Generalized Least Squares (FGLS) model was employed in this study to investigate the role of ownership structure and Sharia compliance in improving the CSR performance of Indonesian mining companies that were operated between 2012 and 2021. The findings reveal that institutional ownership, foreign ownership, and Sharia compliance are essential factors in increasing mining companies’ CSR performance, but state ownership and ownership concentration are not. This study addresses a vacuum in the current CSR literature for mining businesses. Furthermore, it gives extra information and insight for practitioners, including the Indonesian government as the CSR regulator, investors, management, and non-governmental organizations (NGOs). This is one of the first studies to examine ownership structure and Sharia compliance in relation to mining companies’ CSR performance, notably in Indonesia, Feasible Generalized Least Squares.

Alkyl levulinate is a biomass-based chemical compound used as a fuel additive. This research aims to produce ethyl levulinate from levulinic acid and ethanol using esterification with the assistance of a heterogeneous sulfonated carbon catalyst. The carbon sulfonate catalyst is obtained from corncob waste that has undergone carbonization at 300 °C and sulfonation using sulfuric acid at a temperature of 150 °C for 8 h. The catalyst is used for esterification with predetermined operating variables using Box-Behnken Design (BBD) on the response surface methodology (RSM). The result shows significant variables for ethyl levulinate esterification are catalyst loading and esterification time. The FTIR analysis indicates the presence of S=O bonds in the sulfonated carbon catalyst. The XRD and SEM analysis shows that the sulfonated carbon catalyst is in amorphous and mesoporous form. Catalyst reusability demonstrates that the corncob-derived carbon sulfonate catalyst can be used up to 3 times. The optimum condition for esterification is 9 h of reaction, 10 % catalyst loading, and a molar ratio of levulinic acid to ethanol of 1:10, which has 83.15 % conversion. These results present the optimum parameter conditions for an efficient heterogeneous catalyst from corncob for producing ethyl levulinate.

The massive consumption of conventional recyclable products causes environmental pollution, so it is very important to raise public awareness about the use of green plastics. This study assessed a comprehensive understanding of the behavioural intention model of green plastic products from the perspective of the new generation. This study uses data collected from 551 new-generation customers of environmentally friendly recyclable plastic products in Indonesia. Data analysis employing partial least squares reveals that the behavioural intention model, including perceived quality, perceived value, trust, and satisfaction as determinants, is a fit across these generation cohorts. Further, this study claims that customer satisfaction is the main driver of behavioural intention, while trust is the main determinant of satisfaction with green plastic products for both generations. Finally, this study shows that millennial satisfaction is driven by perceived value, whereas new-generation satisfaction is determined by perceived quality. The study only considered behavioural intention, including quality, value, trust, and satisfaction as the drivers, meanwhile, other potential factors could influence the intention significantly as well. These findings specifically apply to green plastic products but not to other kinds of green products. In addition, the government can devise better policies supporting green products by offering tax incentives for recyclable products.

Email serves as the primary mode of communication in today’s interconnected digital world, encompassing business, education, and interpersonal relationships. However, email’s reliance on shared media makes it susceptible to interception and misuse of confidential data. Pretty Good Privacy (PGP) protects the privacy of email contents to address this problem. While PGP offers encryption, its key sharing has weaknesses. Blockchain technology is characterized by its immutability feature. Once information is stored in the blockchain, altering it becomes extremely difficult. This characteristic serves as a valuable defense against weaknesses in the PGP key sharing system. Furthermore, the implementation of smart contracts eliminates the need for a Man-in-the-Middle when sharing keys, thereby improving the security of key sharing and fostering trust among individuals. Blockchain and smart contracts improve security, but privacy remains a concern. To further bolster privacy protection, in this paper we propose the integration of Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARKs) and blockchain into PGP key sharing mechanism. zk-SNARKs enable efficient verification of encrypted data without revealing sensitive information, thus preventing exposure of user privacy. Additionally, we employ Elliptic Curve Cryptography (ECC) in order to guarantee the confidentiality of the PGP key. Through this holistic integration, the security of the PGP key is enhanced, ensuring both confidentiality and integrity while safeguarding user privacy. Furthermore, gas consumption and transaction costs were evaluated with and without zk-SNARKs. The results demonstrate that the proposed mechanism minimizes gas consumption and transaction costs.

Monitoring the health of the elderly using wearable sensors and Internet of Things (IoT) devices necessitates the collection of data from various sources, thereby increasing the volume of data to be gathered at the monitoring center. As previously elucidated, the system exhibits high accuracy in measuring variables such as blood oxygen saturation (BOS) and heart rate (HR), as well as demonstrating proficient accuracy in implementing fuzzy rules to detect the “stable” or “unstable” condition of elderly patients. Therefore, by integrating wearable sensors and IoT devices into the elderly health monitoring system, we can enhance the quality of monitoring and provide more timely healthcare solutions tailored to the elderly population’s needs. The integration of fuzzy rules and IoT technology into the elderly health monitoring system offers an efficient and effective solution for continuous health surveillance. In this research, we integrated fuzzy rules and IoT technology into the elderly health monitoring system using parameters such as BOS and HR, through the integration of MAX30100 sensors and ESP32 microprocessors. The implementation of fuzzy rules resulted in nine rules indicating whether an elderly patient is in a “stable” or “unstable” condition. The methodology involved (1) component preparation, (2) device accuracy analysis, (3) fuzzy rule development, (4) Android-based mobile application development, (5) fuzzy rule accuracy analysis, and (6) cost analysis. Experimental results indicated a device accuracy of 98.89% in measuring BOS and HR variables compared to medical devices and a fuzzy rule accuracy of 96% in detecting whether the patient’s condition is “stable” or “unstable.” Based on the experimental findings, the elderly health monitoring system provides a user-friendly, precise, and cost-effective solution to enhance the quality of life for the elderly population.

Indonesia’s vast maritime territory offers a unique opportunity for harnessing the potential Energy of seawater currents. This study explores the effectiveness of a combined Savonius and propeller-type turbine system. The Savonius turbine, known for its efficiency in capturing ocean currents due to its large sweep area, is combined with a propeller-type turbine to enhance rotational speed and power generation. A novel approach is employed to induce turbulence and optimize energy extraction, first channeling water through the propeller turbine and then into the Savonius turbine. A comprehensive investigation is conducted through simulations and experimental tests within a controlled tunnel environment. The study explores the performance of two-bladed and three-bladed Propeller-Savonius configurations at varying inlet water velocities (0.1, 0.3, 0.6 and 1.0 m/s). The simulation incorporates a turbulence model with 5% intensity and a hydraulic diameter of 0.216 m. Results indicate that the proposed configuration achieves a maximum power output of 2.0293 W with an impressive efficiency of 63.339% in simulation. Concurrently, experimental testing yields a peak efficiency of 61.335% and turbine power of 0.3951 W. The findings demonstrate the feasibility of the combined turbine system and highlight the importance of turbulence in optimizing energy extraction from seawater currents. This research contributes valuable insights into the design and performance of hybrid turbines for harnessing oceanic Energy, emphasizing the potential for sustainable power generation in maritime regions. The methodology and results presented herein offer a foundation for further exploration and refinement of seawater current energy conversion technologies.