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Antioxidant activity test of ethanol extract of red algae (Kappaphycus alvarezii) green variety from north coasts of Jepara district with DPPH method
Get PDFFree radicals are unstable and highly reactive molecules that can cause cells damage. This cell damage can be inhibited by antioxidant compounds. One of the red algae, Kappaphycus alvarezii, is thought to contain phenolics and flavonoids compounds that can b used US antioxidants compounds. this study aims to determine the ethanol extract of red algae (Kappaphycus alvarezii) green variety has antioxidants activity using the DPPH method. this study also aims to determine the IC 50 value of the ethanolic extract of red algae (Kappaphycus alvarezii) green variety. The antioxidant activity test of red algae ethanol extract was carried out using the DPPH method. The results showed that the ethanolic extract of red algae (Kappaphycus alvarezii) green variety had antioxidant activity and the IC 50 value of the ethanolic extract of red algae was 242.28 ppm with a very weakcategory
Inhibitory test of binahong (Anredera cordifolia (Ten.) steenis) n-hexane fraction against bacillus subtillis bacteria by diffusion method
No full textBinahong plants (Anredera cordifolia (Ten.) Steenis) contain alkaloids,flavonoids,saponins, and terpenoids, the chemical compounds of binahong leaves have many antibacterial properties. This study aims to determine the antibacterial inhibition of n-hexane (Anredera cofdifolia Ten.) Steenis) against Bacillus Subtillis. This type of research is experimental descriptive, binahong leaf n-hexane fraction was previously obtained by extraction using maceration method with 70% ethanol solvent obtained by using a 10% DMSO dissolved and tested for antibacterial inhibition with the method of solid well diffusion against Bacillus Subtillis in the series of concentrations of 20%,40%,60% dan 80% positive controls used were chloramphenicol 10% and negative control DMSO 20%. The results of the study showed that n-hexane fraction of binahong leaves (Anreders cordifolia (Ten.) Steenis) was able to inhibit the growth of the bacterium Bacillus subtillis. The greater the concentration used, the greater the results obtained
Analysis on how hotel leaders be role model to staff
Get PDFThis Journal reviews the meaning of Hospitality role models in the figure of a leader. When people hear the word role model they often thought about celebrities or famous historical figure. Little did they know that for some people, their role model is their closest friend, work partner, or even family members. What makes a leader is seen as a role model? Someone who can influence people around them and give them great examples are seen as leaders. A leader must have strong values in them self, they have to be confident in leading people who are still lost or still didn’t know the reason why they are here and what are they for. If a leader is not confident of themself then how will they assure people to be confident and overcome their fear such as insecurities and the fear of failling. A leader shall lead them cause when they are under your supervisory, you are responsible for their actions at some circumstances. A leader has to set a good example all the time for the staff, because staff tend to copy what their role model do. This journal will use qualitative method, by getting reference as a research source. This journal will discuss about how to be a great leader and a role model, how to be more than just someone who rule over people and tells people what to do but to be someone who is admired and is set as an example for others especially to staffs. To give example and description on how to be a great leader is what a leader should do. In conclusion every leader should position themselves not as someone who have a high position and just rule over people, they need to be someone who can make staff comfortable and respect them not just as a leader but also as a role model. Guiding them as if their success is your responsibility is a great mindset a hotel leader should have
Enhancing cirrhosis detection: A deep learning approach with convolutional neural networks
Get PDFCirrhosis, a prevalent and life-threatening liver condition, demands early detection for effective intervention. This study investigates the potential of machine learning algorithms, including Convolutional Neural Networks (CNN), Support Vector Machines (SVM), Decision Trees, K-Nearest Neighbors (KNN), Gaussian Naive Bayes (GNB), and Gradient Boosting (GBoost), in cirrhosis prediction using a dataset from Kaggle containing 418 observations and 20 attributes. Performance evaluation involves metrics like accuracy, precision, recall, and F1-score, revealing CNN's superior performance with an 84% accuracy rate. The study highlights the importance of algorithm selection and feature engineering in medical diagnosis. Moreover, a comparison with traditional machine learning techniques underscores CNN's prowess in this domain. Beyond cirrhosis, CNNs offer promise for automating feature extraction from medical imagery and recognizing complex patterns, potentially transforming diagnostic accuracy in healthcare
Mix histogram and gray level co-occurrence matrix to improve glaucoma prediction machine learning
Get PDFGlaucoma is an eye disease that is the second leading cause of blindness. Examination of glaucoma by an ophthalmologist is usually done by observing the retinal image directly. Observations from one doctor to another may differ, depending on their educational background, experience, and psychological condition. Therefore, a glaucoma detection system based on digital image processing is needed. The detection or classification of glaucoma with digital image processing is strongly influenced by the feature extraction method, feature selection, and the type of features used. Many researchers have carried out various kinds of feature extraction for glaucoma detection systems whose accuracy needs to be improved. In general, there are two groups of features, namely morphological features and non-morphological features (image-based features). In this study, it is proposed to detect glaucoma using texture features, namely the GLCM feature extraction method, histograms, and the combined GLCM-histogram extraction method. The GLCM method uses 5 features and the Histogram uses 6 features. To distinguish between glaucoma and non-glaucoma eyes, the multi-layer perceptron (MLP) artificial neural network model serves as a classifier. The data used in this study consisted of 136 fundus images (66 normal images and 70 images affected by glaucoma). The performance obtained with this approach is an accuracy of 93.4%, a sensitivity of 86.6%, and a specificity of 100%
The application of the tsukamoto fuzzy method in controlling the dryer for shrimp cracker hygienization
No full textThe process of drying crackers is traditionally carried out on the side of the road and open places. The impact of drying on product quality, especially hygiene because it is directly contaminated with dust, pollutants and pathogenic microbes. Drying depends on the sun's heat which affects the continuity of production and the level of drought. How to identify food hygiene using an inductive proximity sensor functions as a metal content detector. Because the metal content when ingested by humans is very dangerous. Drying is affected by temperature, moisture content and capacity. Oven drying application is equipped with an inductive proximity sensor and a DS18B20 temperature sensor. The Fuzzy Tsukamoto method for weight problems is grouped into a separate set. So that it can process oven temperature data. The control system for drying 3 shelves of crackers totaling 250 takes 25.6 minutes, drying 5 shelves of crackers totaling 410 takes 31.6 minutes. The drying process temperature is 30OC-70OC, the temperature used is a minimum of 60OC and a maximum of 65OC. Drying near the maximum temperature experiences a slowdown. If drying is done traditionally with the help of sunlight it takes longer
Digital marketing strategy of kampung UMKM, blora district in attracting tourists in the era of pandemi COVID-19
Get PDFThe rapid development of information technology can bring many advantages in various sectors, one of which is the tourism sector. The advantages offered are carried out to develop micro, small and medium enterprises. This research activity aims to determine the impact of the application of digital media on the development of micro, small and medium enterprises to the Blora MSME Village in order to increase sales and attract tourists in the midst of the difficult Covid-19 pandemic by using digital marketing strategies. The role of technology is needed to suppress the success of a business in expanding the market by utilizing information technology that can be used for modern marketing communication media. The advantages offered by digital media range from cost-effective, wide coverage, and easy access to use by the public. therefore, MSME actors who previously only depended on consumers who came, now MSME actors can now market their products on digital media which is considered very profitable. The results of data collection in two ways, namely by literature review and field research, where the authors find that digital media is often used by MSME actors
Logistics 4.0 operation transformation determinant factors
Get PDFThe phenomenal growth of e-commerce and online purchase have greatly impacted global logistics industry. As a results, integration of Logistics and Industry Revolution 4.0 is inevitable due to increasing complexities and strong needs to fulfill demanding customer responsiveness. The term Logistics4.0 is coined to reflect the integration of smart systems in industrial logistics which transformed the entire logistics operation and it is getting high focus from researchers and industry practitioners. This article focused on the influential factors which contributed towards Logistics4.0 operation transformation. The business feasibility, workforce competency and technology readiness factors were evaluated thoroughly which provided essential and critical insights to the global logistics industry as it embarked towards smart Logistics4.0
Performance Analysis of Wi-Fi Wireless Networks In A Vortex Media Access And Reseller Broadband
Get PDFThe research aims to analyze network performance in an office and also a broadband reseller, to determine network quality through monitoring trials on servers and clients. The research uses data collection methods by conducting interviews. The second stage is needs analysis as a benchmark for network performance analysis. The next stage is monitoring the server and client to determine network speed. From research that has been carried out related to the analysis of WiFi wireless networks in small and medium office environments using custom network topology to suit needs, as well as broadband resellers also using custom network topology. The distribution of bandwidth from each place adjusts to their respective needs to get quality network connections The good thing is, that there are no specific standards for dividing bandwidth, it all depends on needs. The results of the data obtained from the analysis of the two places, of course from the analysis that the author has carried out, we can know the quality of the network connection from the two places, apart from that the topology design used by the office environment and also broadband resellers can increase knowledge about WiFi wireless networks and can be an example to open a business in the field of WiFi wireless networks that can provide faster WiFi performance with wider coverage
Implementation of a faster R-CNN algorithm for identification of metastatic tissue using lymphoma histopathological images
Get PDFProcedures for diagnosis of lymphoma includes blood tests, CT scan or MRI, and histopathological examination through a biopsy. Histopathological examination is the gold standard of diagnosis. Pathology diagnosis of lymphoma is challenging and difficult in the field of diagnostic pathology. This study aims to identify lymph node metastases using the Faster R-CNN algorithm using histopathological images of lymph nodes so that the Faster RCNN system design can help the medical team to make diagnostic decisions. Identification carried out by Faster R-CNN is by classifying histopathological images into normal classes and metastatic classes. Loss values that are not indicated for underfitting and overfitting are shown from the 10th epoch to the 20th epoch. The optimizer and the number of epochs for the optimal value of 83.3% accuracy and 71.8% recall are ADAM with 20 epochs. The accuracy and recall results obtained are quite good. 1113 metastatic images and 1478 normal images were predicted correctly, while 437 metastatic images and 82 normal images were predicted incorrectly