Search Results (183)

The energy transition toward Net Zero Emission by 2060 hinges on the renewable energy power plants in Indonesia. Good practices in several countries suggest a peer-to-peer (P2P) energy trading system using blockchain technology, supported by renewable energy (solar panels), an innovation to provide equal access to sustainable electricity while reducing the impact of climate change. The P2P energy trading concept has a higher social potential than the conventional electricity buying and selling approach, such as that of PLN (the state-owned electricity company in Indonesia), which applies the network management concept but does not have a sharing element. This model implements a solar-powered mini-grid system and produces a smart contract that facilitates electricity network users to buy, sell, and trade electricity in rural areas via smartphones. This study aims to measure the stakeholders’ perceptions of the peer-to-peer (P2P) energy trading model using blockchain technology in the Gumelar District, Banyumas Regency, Central Java Province, Indonesia. The stakeholders in question are representatives of Households (producers and consumers), Government, State Electricity Company (PLN), Non-Governmental Organizations, Private Sector and Academician. Measurement of perception in this study used a questionnaire approach with a Likert scale. The results of filling out the questionnaire were analyzed using four methods: IFE/EFE matrix; IE matrix; SWOT matrix; and SPACE matrix to assess the results and their suitability to each other. The results of the stakeholder perception assessment show that there are 44 internal factors and 33 external factors that can influence this model. We obtained an IFE and EFE score of 2.92 and 2.83 for the internal and external results using the IE matrix. These place the model in quadrant V, meaning the P2P model can survive in the long term to generate profits. Based on the SWOT analysis results, this model is located at the coordinate point −0.40, 0.31, placing it in quadrant II. This means that the P2P model is in a competitive situation and faces threats but still has internal strengths. Based on the SPACE matrix, stakeholder perception states that the P2P model is at coordinate point 1, −0.3. This shows that the P2P model has the potential to be a competitive advantage in its type of activity that continues to grow. In conclusion, our findings show that stakeholders’ perceptions of P2P models using blockchain technology can be implemented effectively and provide social, economic, and environmental incentives. Full article

Dissolved oxygen (DO) is a crucial water quality characteristic in the cultivation of vannamei shrimp. Increasing the DO concentration in shrimp ponds can be carried out using the aeration method with a tool called an aerator. In this study, types of fine-pore aeration tubes are chosen. This aerator offers multiple benefits, such as superior aeration efficiency, effortless installation, and minimal clogging. In practice, fine-pore aeration tubes can be arranged according to needs, so the layout used can influence the resulting aeration performance. This research uses the computational fluid dynamics (CFD) method to analyze DO distribution, water circulation, and aeration performance ($K_L{a}_{20}$, SOTR, and SOTE) produced in various aerator layouts, namely straight-type, ring-type, and square-type, in a vannamei shrimp pond. The results show that the straight-type layout has the best DO distribution because it is spread throughout the pond area. The square-type layout has the best water circulation because it has the largest area with water velocities of less than 5 cm/s. The optimal aeration performance was achieved with the straight-type layout, which demonstrated a $K_L{a}_{20}$ value of 3.16 h⁻¹, SOTR value of 19.20 kg/h, and SOTE of 29.30%. Full article

The Klaten Regency, Central Java Province, Indonesia, is a leptospirosis endemic area. The purpose of this study is to spatially describe the abiotic and biotic environmental factors that contributed to the incidence of leptospirosis in the Klaten Regency in 2018. This was a descriptive observational with a cross-sectional approach conducted in the Klaten Regency, Central Java, in 2019 with 59 respondents. The results revealed that the percentage of abiotic environmental factors such as poor waste disposal facilities, poor gutter conditions, rivers < 200 m, and flooding history, namely 35.6%, 41.2%, 54.2%, and 6.8%, respectively. The highest leptospirosis cases occurred in April 2018, with 325 mm of rainfall, an average temperature of 27 °C, an average humidity of 82.3%, and an altitude of 100–200 MASL (79.7%). Meanwhile, biotic factors included rat nest existence (100%), having pets at risk (32.2%), and ≥three types of vegetation (79.7%). The main result confirmed that all leptospirosis cases had rat nests throughout the respondent’s house. This finding emphasizes the importance of rat pest control programs by establishing cross-sectoral collaboration with the Department of Agriculture and educating the public to also play a role in environmental cleanliness in controlling rats. Full article

X-ray fluoroscopy causes relatively high radiation exposure to physicians, radiation professionals, and patients. Understanding the behavior of scattered radiation is crucial for reducing occupational exposure. We developed a system for estimating radiation exposure during fluoroscopy by monitoring the position of the physician using a depth camera for radiation protection education. The dose distribution of scattered radiation in an X-ray room was simulated using Monte Carlo code. The data were displayed using augmented reality markers, and the dose at each joint point location was estimated using body tracking. Additional functions were created, such as displaying arbitrary two-dimensional cross-sections. The system performance ranged from 9.0 to 11.0 FPS with or without motion and a protective apron. The estimated doses were 0.93 to 1.21 times the measured doses for all joint points, except for the chest and pelvis. The estimated doses for the chest and pelvis were lower than the measured dose, with the minimum values being 0.72 and 0.60 times lower for the chest and pelvis, respectively. The system provides valuable insight into the estimation of radiation dose at joint points based on the physician’s position and movements, the physician’s optimal fluoroscopy location, and warning of dangerous exposure doses. Full article

A method to determine aceclofenac, ketorolac, and sulindac in human urine samples using microemulsion electrokinetic chromatography (MEEKC) has been developed in this study. The optimization of MEEKC conditions was carried out by changing the microemulsion compositions including the buffer pH, borate salt concentration, surfactant concentration, co-surfactant concentration, organic modifier concentration, and oil droplet concentration. The optimum separation of selected drugs was obtained with a composition of microemulsion containing 10 mM borate buffer pH 9, 0.5% sodium dodecyl sulphate (SDS), 6.6% n-butanol, 6.0% acetonitrile, and 0.8% ethyl acetate. Excellent linearity was obtained in the range concentration of 25 to 200 ppm with r² > 0.999. Limits of detection (LOD, S/N = 3) and limits of quantification (LOQ, S/N = 10) were 2.72 to 4.75 and 9.08 to 15.85 ppm, respectively. The solid-phase extraction (SPE) method using C-18 as an adsorbent and the solid phase micro-tip extraction (SPMTE) method using multiwalled carbon nanotubes (MWCNTs) as an adsorbent were used to clean-up and pre-concentrate the urine samples prior to the MEEKC analysis. The best recoveries of the selected drugs in the spiked urine sample were 91 to 103% with RSD of 1.26 to 4.03% (n = 3) using the SPE-MEEKC method. Full article

Dissatisfaction among upper limb prosthetic users is high, reaching over 70%, and 52% of upper limb amputees abandon their prosthetic devices due to limitations such as limited functionality, poor design/aesthetic, and improper fit. The conventional procedure of making prosthetics is time-consuming and expensive. This study was conducted to provide an alternative solution for the several issues of current prosthetic devices. 3D printing technology offers a promising alternative, providing greater accuracy, reduced labor time, and improved fit and comfort. This research explores the application of 3D printing for creating custom silicone prosthetic fingers, using Fused Deposition Modelling (FDM) for the mold. A high-resolution 3D scanner was employed to capture the precise anatomy of the patient’s hand, and CAD software was used to design molds that satisfied the patient preference and were reusable. The resulting prosthetics demonstrated good fit and patient satisfaction, though exact color matching remains a challenge, but still, it did demonstrate that it is possible to fabricate colored prosthetics. Performance tests, such as the Jebsen–Taylor Hand Function Test, indicated that while initial performance with the prosthetic was slightly lower, patient satisfaction and potential for improved functionality over time were high. This study underscores the potential of 3D printing to enhance the customization, cost-effectiveness, and overall quality of prosthetic devices, contributing to Sustainable Development Goals related to health and industry innovation. Full article

This research improves the strength of plastic using avocado seed starch and PLA. The effect of blending avocado seed starch and PLA was optimized using the RSM approach by using two variables: water absorption and biodegradability. Mixing them using RSM gave the best result: 1.8 g of starch and 3 g of PLA. Degradable plastic has a tensile strength of 10.1 MPa, elongation at a break of 85.8%, and a Young’s modulus of 190 MPa. Infrared spectroscopy showed that the plastic had a -OH bond at 3273.20 cm⁻¹, 3502.73 cm⁻¹, and 3647.39 cm⁻¹, a CH₂ bond at 2953.52 cm⁻¹, 2945.30 cm⁻¹, and 2902.87 cm⁻¹, a C=C bond at 1631.78 cm⁻¹, and a C-O bond at 1741.72 cm⁻¹. The plastic decomposed in the soil. It was organic and hydrophilic. Thermal tests demonstrated that the plastic can withstand heat well, losing weight at 356.86 °C to 413.64 °C, forming crystals and plastic melts at 159.10 °C—the same as PLA. In the melt flow test, the sample melted before measurement, and was therefore not measurable—process conditions affected it. A water absorption of 5.763% and biodegradation rate of 37.988% were found when the samples were decomposed for 12 days. The starch and PLA fused in the morphology analysis to form a smooth surface. The RSM value was close to 1. The RSM gave the best process parameters. Full article

Hospitality services play a crucial role in shaping tourist satisfaction and revisiting intention toward destinations. Traditional feedback methods like surveys often fail to capture the nuanced and real-time experiences of tourists. Digital platforms such as TripAdvisor, Yelp, and Google Reviews provide a rich source of user-generated content, but the sheer volume of reviews makes manual analysis impractical. This study proposes integrating aspect-based sentiment analysis with zero-shot learning to analyze online tourist reviews effectively without requiring extensive annotated datasets. Using pretrained models like RoBERTa, the research framework involves keyword extraction, sentence segment detection, aspect construction, and sentiment polarity measurement. The dataset, sourced from TripAdvisor reviews of attractions, hotels, and restaurants in Central Java, Indonesia, underwent preprocessing to ensure suitability for analysis. The results highlight the importance of aspects such as food, accommodation, and cultural experiences in tourist satisfaction. The findings indicate a need for continuous service improvement to meet evolving tourist expectations, demonstrating the potential of advanced natural language processing techniques in enhancing hospitality services and customer satisfaction. Full article

This paper presents the results of borehole investigations and laboratory tests carried out to characterize the soils derived from in situ weathering of tuff in Central Java, Indonesia. The 70 m thick weathering profile of the Quaternary tuff consisted of residual soil and completely to highly decomposed rocks. The relatively low dry unit weight and cohesion but high water content, porosity, plastic and liquid limits, and angle of internal friction of the soils in the present study were related to the dominance of halloysite clay minerals. The established relationships to predict soil shear strength parameters from the soil plasticity index and standard penetration test (SPT) N-values were examined, and linear and non-linear relationships for soils derived from in situ weathering of tuff were proposed. Full article

In recent advancements in agricultural technology, quantum mechanics and deep learning integration have shown promising potential to revolutionize rice yield forecasting methods. This research introduces a novel Hybrid Quantum Deep Learning model that leverages the intricate processing capabilities of quantum computing combined with the robust pattern recognition prowess of deep learning algorithms such as Extreme Gradient Boosting (XGBoost) and Bidirectional Long Short-Term Memory (Bi-LSTM). Bi-LSTM networks are used for temporal feature extraction and quantum circuits for quantum feature processing. Quantum circuits leverage quantum superposition and entanglement to enhance data representation by capturing intricate feature interactions. These enriched quantum features are combined with the temporal features extracted by Bi-LSTM and fed into an XGBoost regressor. By synthesizing quantum feature processing and classical machine learning techniques, our model aims to improve prediction accuracy significantly. Based on measurements of mean square error (MSE), the coefficient of determination ($R^2$), and mean average error (MAE), the results are 1.191621 × 10⁻⁵, 0.999929482, and 0.001392724, respectively. This value is so close to perfect that it helps make essential decisions in global agricultural planning and management. Full article

In recent decades, Indonesia has experienced a surge in natural disasters, resulting in increased casualties and disruptions to economic growth and welfare. This study investigates the impact of various types of natural disasters, focusing on how economic growth (measured by provincial GDP) and welfare levels (measured by the Human Development Index, HDI) influence the number of victims affected by extreme weather. Data on gross regional domestic product and the Human Development Index for each province in Indonesia were obtained from Statistics Indonesia. We employed multivariable negative binomial regression to analyze the relationships between the number of victims affected by extreme weather, provincial HDI, and provincial GDP. The results indicate significant correlations between provincial GDP, HDI, and the number of victims. Higher HDI correlates with fewer victims, whereas higher GDP is associated with an increase in victims. Additionally, we used the Self-Organizing Map (SOM) method, identifying two clusters as the optimal model. Cluster 1 comprises 31 provinces, while Cluster 2 comprises 3 provinces, with the latter highlighting the provinces with the highest disaster risk. Consequently, provinces such as West Java, Central Java, and East Java require heightened attention from various stakeholders involved in disaster management efforts. By examining these relationships, our study contributes to the understanding of sustainable development and resilience against natural disasters. It underscores the importance of improving welfare and economic policies to mitigate the impacts of extreme weather events. Full article

In this study, the potential role and interaction of the APOε and KLOTHO genes on the penetrance of fragile X-associated tremor/ataxia syndrome (FXTAS) and on the IQ trajectory were investigated. FXTAS was diagnosed based on molecular, clinical and radiological criteria. Males with the premutation (PM) over 50 years, 165 with and 34 without an FXTAS diagnosis, were included in this study and were compared based on their APO (ε2-ε3-ε4) and KLOTHO variant (KL-VS) genotypes. The effect of APOε4 on FXTAS stage and on diagnosis did not differ significantly by KL-VS genotype with interaction effect p = 0.662 and p = 0.91, respectively. In the FXTAS individuals with an APOε2 allele, a marginal significance was observed towards a larger decline in verbal IQ (VIQ) in individuals with an APOε4 allele compared to those without an APOε4 allele (p = 0.071). In conclusion, our findings suggest that the APOε4 and KL-VS genotypes alone or through their interaction effect do not appear to predispose to either FXTAS diagnosis or stage in male carriers of the PM allele. A further study is needed to establish the trend of IQ decline in the FXTAS individuals who carry APOε4 with APOε2 compared to those without APOε4. Full article

Programmable Logic Controllers (PLCs) are indispensable for current and future industrial development, especially in smart factories, smart home technology, automated production lines, and machinery manufacturing. This study presents the trends in PLC software and hardware development through a technology roadmap and offers relevant suggestions to help industries achieve sustainable development, enhance market competitiveness, and provide references for research. Through expert interviews and fuzzy Delphi analysis, this study points out that future PLC development needs to focus on editing interfaces, syntax, Central Processing Units, Memory Units, and Communication Modules. Specific recommendations include visualizing regional/global label settings and connection settings, adding Python, JAVA, LabVIEW, and Scratch syntax, improving instruction execution speed, expanding program and expansion capacities, and adopting dual-channel Ethernet and connections to external networks and wireless networks. Fuzzy hierarchical analysis shows that Communication Modules are the most important component, followed by Central Processing Units and syntax expansion, and, finally, program and expansion capacity enhancements. These suggestions aim to promote product innovation and social environment demand evaluation, enhance product competitiveness, and achieve sustainable development goals. Full article

In the context of global efforts to transition toward renewable energy and reduce greenhouse gas emissions, geothermal energy is increasingly recognized as a viable and sustainable option. This paper presents a comprehensive assessment derived from a subset of a larger sample collection within the Dunántúli Group of the Pannonian Basin, Hungary, focusing on optimizing micro-computed tomography (µ-CT) resolution for analyzing pore structures in sandstone formations. By categorizing samples based on geological properties and selecting representatives from each group, the study integrates helium porosity and gas permeability measurements with µ-CT imaging at various resolutions (5 µm, 2 µm, and 1 µm). The findings reveal that µ-CT resolution significantly affects the discernibility and characterization of pore structures. Finer resolutions (2 µm and 1 µm) effectively uncovered interconnected pore networks in medium- to coarse-grained sandstones, suggesting favorable properties for geothermal applications. In contrast, fine-grained samples showed limitations in geothermal applicability at higher resolutions due to their compact nature and minimal pore connectivity, which could not be confidently imaged at 1 µm. Additionally, this study acknowledges the challenges in delineating the boundaries within the Dunántúli Group formations, which adds a layer of complexity to the characterization process. The research highlights the importance of aligning µ-CT findings with geological backgrounds and laboratory measurements for accurate pore structure interpretation in heterogeneous formations. By contributing vital petrophysical data for the Dunántúli Group and the Pannonian Basin, this study provides key insights for selecting appropriate µ-CT imaging resolutions to advance sustainable geothermal energy strategies in the region. The outcomes of this research form the basis for future studies aimed at developing experimental setups to investigate physical clogging and enhance geothermal exploitation methods, crucial for the sustainable development of geothermal resources in the Pannonian Basin. Full article

The phytoplankton size structure exerts a significant influence on ecological processes and biogeochemical cycles. In this study, the interannual variations in remotely sensed phytoplankton size structure in the southern Tropical Indian Ocean (TIO) and the underlying physical mechanisms were investigated. Significant interannual fluctuations in phytoplankton size structure occur in the southeastern TIO and central southern TIO and are very sensitive to Indian Ocean Dipole (IOD) events. During positive IOD events, the southeast wind anomalies reinforce coastal upwelling off of Java and Sumatra, leading to a shift toward a larger phytoplankton structure in the southeastern TIO. The anomalous anticyclonic circulation deepened the thermocline and triggered the oceanic downwelling Rossby waves, resulting in a smaller phytoplankton structure in the southwestern TIO. During the decay phase of the strong positive IOD events, the sustained warming in the southwestern TIO induced basin-wide warming, thereby maintaining such an anomalous phytoplankton size structure into the following spring. The response of phytoplankton size structure and ocean dynamics displayed inverse patterns during the negative IOD events, with an anomalous larger phytoplankton structure in the central southern TIO. These findings enhance our understanding of phytoplankton responses to climate events, with serious implications for ecosystem changes in a warming climate. Full article