Antioxidant Activity and Compound Analysis Using Various Types of Solvents on Cascara Pulp Arabica Gayo Coffee to Treat Skin Aging

Cascara dry coffee skin (coffee cherry tea) is one of the waste products of dried coffee pulp, which is useful as an inhibitor of free radicals, protects the stomach, and is beneficial for the skin. One that can inhibit free radicals is antioxidants. This study assessed the effect of different solvents on Arabica Gayo coffee pulp cascara's antioxidant activity and analyzed the components of Arabica Gayo coffee pulp compounds. This study's experimental methods include cascara extraction, antioxidant assay, and metabolite identification by GCMS analysis. Water, ethanol, methanol, n-hexane, and ethyl acetate were used to extract the cascara Arabica Gayo coffee, then the various concentration of extract was prepared and tested with DPPH solutions. Extracts also identified their secondary metabolites by using GCMS analysis. The antioxidant assay revealed all extracts showed DPPH reduction with performing by changing color into a yellow color. A high concentration of extract positively correlated with percent DPPH inhibition. The highest antioxidant was the ethanol extract of cascara, followed by n-hexane, water, methanol, and ethyl acetate. The metabolites profile of each extract might cause different antioxidant activities. Metabolite profiles showed caffeine in all extracts, with the highest concentration in the n-hexane extract. Hexadecenoic acid was dominated at n-hexane extract, methanol, and ethyl acetate showed unique compounds, quinic acid in methanol and 1(2H)-Naphthalene, octahydro-4a,8a-dim at ethyl acetate extract. Both reported potential antioxidant activity. In summary, ethanol was recommended solvent with high antioxidant performance

Prediction of Drug Demand Based on Deep Learning Approach and Classification Model

The high demand for drugs in the last period has caused problems with drug shortages in several pharmacies. Almost all pharmacies experience the same problem, causing many people who do not to get their drug needs during the current pandemic. To overcome this, analyzing the process of predicting drug demand in the next period is necessary. The prediction process can be used as an initial solution in solving problems to see the number of drug demand numbers that will occur. This study aims to develop a predictive analysis model for drug demand using a deep learning approach and a classification model. Deep learning is an approach that does well in the case of prediction. The classification model also includes the right concept for solving the problem. The prediction and classification analysis methods include K-Means clustering, Multiple Linear Regression (MRL), Artificial Neural Network (ANN), and Decision Tree algorithms C.45. This method can provide better performance results in the prediction process to get precise and accurate output. Prediction results obtained from the learning process provide an accuracy rate of 99.99%. The output of the classification model also provides an overview of the knowledge base in the form of a decision tree. The level of classification model testing carried out gives the accuracy of the classification pattern of 97.05% so that the analytical model developed can predict future drug demand

Analysis of Dam Break Wave Using Analytical, Computational Fluid Dynamics, and Experimental Approaches

This research aims to examine the capability of the Computational Fluid Dynamics (CFD) method in simulating the behavior of dam break waves. It begins by building a 2D numerical simulation using OpenFOAM. To overcome the influence of turbulence, we employed the Large Eddy Simulation (LES) turbulent model, specifically the k-Equation and Smagorinsky model. The simulation was developed by applying the Navier-Stokes equations using the finite volume method in OpenFOAM. The analysis focuses on the free surface of a dam break. The results are in good accordance with both analytical and experimental results. The simulation has followed the trend of experimental and analytical free surface profiles at the dam break’s early and late conditions. The low mesh number on the computational domain caused significant differences in the wavefront of the dam break. It reduced the accuracy of the calculation between the water and air interface. This study highlights the importance of understanding dam break wave behavior as part of risk mitigation for dam leakage. The behavior of dam break waves can be observed by determining observation positions at different locations, with the water gate of a dam serving as the reference point. These highly accurate numerical results indicate that the CFD approach employing OpenFOAM can be relatively cost-effective yet accurate in analyzing multiphase problems, such as dam breaks. This CFD approach is expected to contribute to developing mitigation and disaster prevention in the future

Robust Pose Estimation of Pedestrians with a Deep Neural Networks

In this paper, we provide a method for robust estimation of pedestrian pose that is especially useful for autonomous vehicles traveling toward pedestrians far away. Pedestrians in the far distance appear relatively small when seen by a camera, making it difficult to estimate the pedestrian's pose. We use fused deep neural networks (DNNs) to resolve the problems presented by pedestrians in the far distance. First, DNNs are used to detect pedestrians and enlarge the observed image. Next, the DNN method of pose estimation is applied. The proposed method uses a single camera to estimate the posture of a pedestrian in the far distance. Far-off pedestrians observed by cameras in moving cars appear as low-resolution images of non-rigid bodies. Detection and orientation estimation are difficult with conventional image processing methods. We used a series of DNNs to detect pedestrians, improve data availability, and estimate challenging postures to address these limitations. In this paper, we propose a method based on the multi-stage fusion of DNNs to solve a difficult problem for a single DNN. The experimental results established the superiority of the proposed method when applied to data challenging for conventional pose estimation methods. Applications of the proposed method include observing small objects and objects in the far distance. The method may be especially useful in surveillance systems, sports broadcasting, and other applications requiring human posture estimation

Size Identify Local Culture for Developing Sustainability Construction in SEZ Likupang

In the development of modern construction, the sustainable construction approach has grown in importance. Economic, environmental, and social factors have been identified as influencing its implementation. The use of the sustainable construction method is affected by several additional factors. This study aimed to determine how the Likupang SEZ’s local cultural factors affected sustainable construction methods. The method used is a quantitative study with a sample of the Likupang SEZ in North Sulawesi. The results of this study indicate an influence of local cultural factors of 0.264 on the implementation of the sustainable construction approach in the Likupang SEZ. The results of this study also indicate that local cultural factors are important to consider in implementing sustainable construction. Things that focus on local culture in planting trees as materials for construction, local heritage, Work Culture, and the migrant community environment should be of particular concern in implementing a sustainable construction approach in the Likupang SEZ area. Cultural factors have an important role in ensuring development with this sustainable construction approach considering environmental, social, and economic factors as well as cultural factors as new factors identified as having an influence. This study concludes that it is very important to pay attention to local cultural factors that influence the implementation of a sustainable construction approach in the Likupang SEZ project in North Minahasa Regency, North Sulawesi, Indonesia

Effect of AVG on Anthocyanin and Antioxidant Activity of Bignay Fruit Juice

Consumption of fruit juices product containing various bioactive compounds that are good for health is a current trend. Bignay fruit is a tropical fruit that contains high anthocyanin and can increase its antioxidant ability by adding aloe vera gel (AVG). Bignay fruit also contains organic acids, namely gallic, ferulic, and ellagic acids. AVG is associated with many transparent or colorless polysaccharides and contains functional bioactive chemical compounds. This research aimed to evaluate the effect of AVG concentration on the anthocyanin and antioxidant activity of bignay fruit juice. This research design used a completely randomized design of one factor, namely the concentration of AVG. The formulation of bignay fruit juice with the addition of AVG at concentrations of 25%, 50%, and 75% at a temperature of (6±1) °C was carried out. The observed variables included total anthocyanins, total flavonoids, vitamin C, antioxidant activity, viscosity, and acidity. All experimental units were repeated three times. Periodic observations of bignay fruit juice were carried out on storage 0, 3, 6, 9, 12, and 15 days. The AVG concentration significantly affected the total anthocyanin, antioxidant activity, and viscosity of bignay fruit juice. The best formula for bignay fruit juice is the addition of AVG with a concentration of 25%. The bignay fruit juice notes a large number of functional compounds until the ninth day of storage. Bignay fruit juice can be a recommendation for health-conscious consumers to fulfill their functional drink desires

Decision Support System in Fisheries Industry: Current State and Future Agenda

Decision Support Systems (DSS) are systems that assist decision-makers and aim to synthesize domain and technical knowledge and package it so non-scientists can use and comprehend it. This study aims to compile initial empirical studies that can objectively reject or confirm the central hypothesis. The materials were retrieved after applying the filtered query across all sources. All search engine providers use five query strings. In each example, five findings were collected, sorted, and compared to one another, and 152 papers were generated. Seventy-six documents were discovered after applying the inclusion and exclusion criteria. Each of the 70 papers was independently examined and analyzed. The method of study followed a specific procedure explicitly developed to minimize the risk of researcher bias. It is primarily concerned with whether fisheries have decision-making systems and what empirical outcomes these systems produce, particularly in real-time analysis. The result shows a dearth of research on intelligent DSS, which accounts for less than 3% of all DSS types discussed in the article. This study offers academics and professionals an overview of the implementation of DSS. These new contributions imply the form of several different new contributions to further research. Furthermore, the possibility of identifying research gaps increases once merged with geoinformation technology or spatial information. We introduced a new model that combines spatial logistics techniques with GIS-based tracing and tracking. The envisioned logistics ensure spatial and logistical traceability in the process of fish products

The Effect of Consequences in Utilizing Real Estate Investment Trust (REIT) on Property Development

There are many financing sources in the property development investment process. Conventional financing often produces an un-optimal and unprofitable cost of capital. Real Estate Investment Trust (REIT) is one of the alternative financings that has been applied in global property projects. This financing strategy can be used as an option in property development in Indonesia. Real estate companies in Indonesia understand the development of REITs and also the advantages of using REITs. But still doubtful about the implementation. This study examines the consequences of using REIT and its influence on financing for developers. Two research methods were carried out. The first is a meta-analysis to determine the consequences of using REITs based on previous research, and the second is a questionnaire survey to confirm the results of the meta-analysis to the respondents of developer companies in Surabaya. Data were then analyzed using multiple linear regression. The findings indicate that the consequences of REITs are tax advantage, financial report transparency, 90% dividend distribution obligations, and the need to enter the capital market or acquire property. Then from the statistical results, it is found that the necessity to enter the capital market or acquire property is the most significant consequence of the decision to use REIT. These consequences affect the decision to use REIT by 40.4%, which means that the effect is considered weak, and all of the independent variables positively influence the dependent variables

Designing Web-Based Knowledge Building for Pedagogical Content Knowledge Development of Prospective Teachers

Prospective teachers need to be competent in teaching mathematics. Web-based Knowledge Building is designed to train prospective teachers to have knowledge and skills in teaching mathematics to elementary students. The research and development studies using the ILDF model consist of three phases: exploration, enactment, and evaluation. In the exploration phase, 175 prospective teachers respond 5 points Likert scale for need analysis. We get information that prospective teachers have moderate abilities and conceptual knowledge but high abilities in procedural knowledge. Also, they highly intend to improve their competence in teaching mathematics. They have high skills in learning in an online environment. In the enactment phase, the Moodle application was designed and developed Web-based building knowledge running by LMS. Arithmetic’s instruction course installed in LMS organized in 16 sessions and facilitated by document video, and quiz. The prototype was validated by three subject matter and three learning media experts. In the evaluation phase, the prototype was validated by 40 prospective teachers. The results were that the prototype has a higher score in easy to use, subject matter organizing, adequacy and breadth of subject matter, and benefit. In conclusion, web-based knowledge building is valid and appropriate for developing prospective teacher education. The web-based knowledge building is advantaged in information access, collaboration, knowledge construction, and learners’ responsibility in knowledge acquisition

SARS-Corona Virus Type-2 Detection of Cohabiting Feline with COVID-Positive Individuals in Bandung, Indonesia

Since people and domesticated animals have lived together for a long time, it is possible that diseases could be spread by accident, as happened with SARS-CoV-2. There have been reports of cats in Italy, Spain, and France being exposed to SARS-CoV-2. Not much is known about how farmed animals were exposed to SARS-CoV-2 in Indonesia, which was named the epicenter of COVID-19 in July 2021. The study's goal was to determine if SARS-CoV-2 was present in felines living with people who had COVID-19 in the Bandung, Indonesia, area. Nineteen felines were used in the study. These felines came from seven people who had tested positive for COVID-19. For RT-qPCR testing, samples were taken from the nose, oropharynx, and rectal areas. Blood sera were taken for quick IgM/IgG antibody tests for SARS CoV-2. Using RT-qPCR on nasopharyngeal samples from the felines being studied, it has been seen that four of them have tested positive. But it is interesting to note that only one of these people could be found using a rectal test. There was no clear sign of antibody formation when IgM/IgG rapid test results from blood samples were looked at. The felines that showed positive results were very close to their caretakers and had symptoms that were similar to those of influenza. The results of our study show that there is a chance that SARS-CoV-2 could be passed on to felines who live with people who have COVID-19. Because of this finding, more study needs to be done in this area