Journal of Computer Networks, Architecture and High Performance Computing
Not a member yet
473 research outputs found
Sort by
Revolutionizing Healthcare: How Deep Learning is poised to Change the Landscape of Medical Diagnosis and Treatment
Get PDFDeep learning has become a significant tool in the healthcare industry with the potential to change the way care is provided and enhance patient outcomes. With a focus on personalised medicine, ethical issues and problems, future directions and opportunities, real-world case studies, and data privacy and security, this review article investigates the existing and potential applications of deep learning in healthcare. Deep learning in personalised medicine holds enormous promise for improving patient care by enabling more precise diagnoses and individualised treatment approaches. But it's important to take into account ethical issues like data privacy and the possibility of bias in algorithms. Deep learning in healthcare will likely be used more in the future to manage population health, prevent disease, and improve access to care for underprivileged groups of people. Case studies give specific examples of how deep learning is already changing the healthcare industry, from discovering rare diseases to forecasting patient outcomes. To fully realize the potential of deep learning in healthcare, however, issues including data quality, interpretability, and legal barriers must be resolved. Remote monitoring and telemedicine are two promising areas where deep learning is lowering healthcare expenses and enhancing access to care. Deep learning algorithms can be used to analyse patient data in real-time, warning medical professionals of possible problems before they worsen and allowing for online discussions with experts. Finally, when applying deep learning to healthcare, the importance of data security and privacy cannot be understated. To preserve patient data and guarantee its responsible usage, the appropriate safeguards and rules must be implemented. Deep learning has the ability to transform the healthcare industry by delivering more individualised, practical, and efficient care. However, in order to fully realize its promise, ethical issues, difficulties, and regulatory barriers must be solved. Deep learning has the potential to significantly contribute to enhancing patient outcomes and lowering healthcare costs with the right safeguards and ongoing innovatio
Risk Analysis of Information Security in Balikpapan International Airport Service Desk Plus (SDP) Using The Octave Allegro Method
Get PDFIndonesia, as a developing country, is not exempt from the advancements in information and communication technology. However, these advancements in information and communication technology can bring negative impacts, such as an increasing threat of misuse. SDP (Service Desk Plus) is a system that serves as a management tool for IT services, facilitating employees from various departments in requesting services and reporting ICT (Information Communication Technology) incidents. SDP has faced challenges or obstacles that have hindered its optimal use, such as IT services experiencing downtime, inaccessible ICT services, and SDP users frequently sharing usernames and passwords. Based on these threats, it is necessary to conduct a further analysis of information security risks regarding the security of implementing SDP centrally using the OCTAVE Allegro method. OCTAVE Allegro is a framework that utilizes the OCTAVE approach with a primary focus on information assets, designed to provide faster results without requiring in-depth knowledge of risk assessment. The results of this research identified three risks that can be mitigated, namely user data password errors with a relative risk score of 27, internet downtime with a relative risk score of 31, and file intrusion with a relative risk score of 38, considering the likelihood of threats occurring. Additionally, there is one accepted risk, which is the input error of incident data, with a relative risk score of 19
Enterprise Architecture Design and Implementation for IoT Integration in Manufacturing Electrical Panels
Get PDFInternet of Things technology has transformed manufacturing efficiency and optimization. Electrical panel manufacturing benefits from Internet of Things for better functionality, predictive maintenance, and smoother operations. This study examines the design and implementation of an Enterprise Architecture strategy for seamless Internet of Things integration in electrical panel manufacturing. This research aims to explain Enterprise Architecture and use it as a framework for Internet of Things integration in electrical panel manufacturing. This study examines the complex relationships between Internet of Things components, their connectivity, and a broad Enterprise Architecture framework needed to organize their functionality. This integration uses Enterprise Architecture principles to optimize resource use, reduce downtime, and improve manufacturing efficiency. This effort involves analyzing existing infrastructure, identifying Internet of Things deployment points, and creating an Enterprise Architecture plan that meets business goals. This research emphasizes the need for close IT-operations collaboration to achieve a unified vision and smooth Internet of Things integration. This research addresses Internet of Things implementation challenges in manufacturing, including security, data interoperability, and scalability. Strong governance and adaptable architecture are stressed to address these challenges within an Enterprise Architecture framework. This research aims to help electrical panel manufacturers harness the transformative power of the Internet of Things. Strategic Enterprise Architecture helps businesses navigate complexity, leverage Internet of Things, and create a more agile, connected, and optimized manufacturing landscape
Comparison Accuracy of CNN and VGG16 in Forest Fire Identification: A Case Study
Get PDFThe current research aims to assess the precision of forest fire detection using CNN and VGG16 models, specifically in the context of fire identification. While both models have demonstrated significant promise in visual pattern recognition, a comprehensive analysis regarding their specific benefits in forest fire identification is still needed. The rationale behind this research stems from the significance of promptly identifying forest fires as a preemptive measure to mitigate their detrimental effects on the environment and society. The employed approach involves the application of transfer learning techniques on a diverse and extensive dataset encompassing different forest fire scenarios. The dataset was used to train both CNN and VGG16 models. The test results indicated that the CNN model achieved a forest fire detection accuracy of 96%, while VGG16 achieved 98% accuracy. The primary objective of this research is to enhance comprehension regarding the merits and demerits of each model in the context of forest fire identification scenarios. While VGG16 exhibits marginally superior performance in identifying forest fires, this discrepancy offers valuable insight into the practical applicability of these two models for fire detection in real-world scenarios. These findings establish a solid basis for the advancement of more dependable and efficient early detection technology in the prevention and management of forest fires in the future. This can be accomplished by capitalizing on the unique capabilities of each model to optimize their performance in practical scenarios
Implementation of ColorSpace, GrabCut, and Watershed Methods on Digital Image Segmentation of Coral and Fish Objects
Get PDFPoor coral reefs rising in eastern Indonesia. The colors have disappeared from the seafloor instead, bleached branches are visible. To recognize the differences between dead and healthy coral reefs, an identification system has been created using the image processing method. Object segmentation is a step in digital image processing to separate one object from another based on specific characteristics. In this study, coral objects with various colored backgrounds and things became a problem to separate, so this study aimed to separate these various colors. This research uses color space segmentation to visualize RGB and HSV colors, Grabcut segmentation to separate the largest corals, and watershed segmentation to separate dead corals. Therefore, from this study, the RGB and HSV color visualizations were clearly visible. From Grabcut segmentation, it is found that the largest fish is detected and can be displayed in the segmentation results. At the same time, the watershed segmentation displays dead coral taken by gray segmentation with otsu
Comparison of Machine Learning Techniques in the Classification of Parkinson’s Desease Sufferers
Get PDFParkinson's disease is a progressive and relatively common neurodegenerative disorder in the central nervous system where sufferers can have difficulty moving. This disease has a high mortality rate in the world of around 9.3 million in 2021. Meanwhile, in Indonesia, it is estimated that as many as 12,980 people die every year due to Parkinson's cases. This increase in cases of death is due to the lack of information about the initial symptoms and dangers of the disease, besides it is important to know how to prevent it early. Early detection of Parkinson's disease can prevent symptoms of a certain age thereby increasing life expectancy. The existence of a computer-based system for diagnosing Parkinson's disease is called a classification system where the system applies the Machine Learning method. This study aims to compare the performance of algorithms in the classification system of people with computer diseases. In this study, it used methods in Machine Learning such as K-NN, Multi Layer Percepteron (MLP), Linear Regression and Support Vector Machine (SVM). The data set in this study was obtained using the Weka application. The dataset used was Parkinson's Disease data totaling 195 rows of data taken from the UCI Machine Learning Repository Datasets. The results of the experiment based on the four algorithms showed that the poor performance was the Multi Layer Percepteron approach to regression data with an RSME value of 0.459. Meanwhile, the k-Neural Network Algorithm is a good classification technique forParkinson's problem with an RMSE value of 0.1895
Election of Cooperative Chairman Using the Moora Method (Multi Objective Optimization On The Basis Of Ratio Analysis)
No full textThe Padrepio Helvetia Medan Parish Mandiri Savings and Loans Association Cooperative is one of the cooperatives engaged in the savings and loan sector by prioritizing members' desire to save so that they can create joint capital for members to borrow with appropriate loan services for welfare purposes. The Annual Members' Meeting is an annual agenda as a media for management to be accountable for their performance for one year. The chairman of the cooperative is the highest structural position of the administrator who has duties and responsibilities both inside and outside the cooperative in controlling all cooperative activities. The process of electing the chairman of the Padre Pio Parish Savings and Loans Association cooperative is still being carried out only by pointing to and mentioning someone's name from among the names of the management and then conveying it to members to approve. The determination of the chairman which is carried out using the arbitrary model is not in accordance with the terms and criteria of an optimal cooperative chairman because the elected chairman is not necessarily the most competent of the candidates and often happens just because of friendship so the results are not objective. With the reasons described, the researcher applied the MOORA method. The application of the MOORA method to the election of the chairman of the Padre Pio Helvetia Medan Parish Independent Savings and Loans cooperative can help determine a more objective chairman based on terms and criteria by solving problems through complex mathematical calculations, determining the weight value for each attribute, then proceed with the ranking process which will select the alternative that has been given. In this study the criteria determined consisted of background and educational level, certificate ownership, age, and length of time being a member. In the objective approach, the weight value is calculated mathematically so that it ignores the subjectivity of the decision maker. With the application of the MOORA method, several alternatives that meet the requirements and criteria can be determined which is the best to serve as chairman. The best ranking results are those who are most worthy of being the head of a more objective cooperative
Researchers Productivity Level Clustering Based On H-Index and Citation Using The Fuzzy C-Means Algorithm
Get PDFThe fuzzy C-Means algorithm is a partition-based clustering algorithm.Fuzzy C-Means is very helpful in modeling data whose distribution has outliers. Outliers are where there is a data object that is far apart from the existing clusters. Fuzzy C-Means groups data by minimizing the membership function of a data set. so that each piece of data can be a member of more than one group. In this study, the dataset used was the paper citation vs. H-index dataset in the Kaggle.com repository. This dataset is known to have outliers in fuzzy C-Means and has better performance compared to the K-Means and K-Medoid algorithms in modeling datasets that have outliers
Serious Games About Indonesia’s Heroes Day for Education About Events 10 November 1945
Get PDFHeroes' Day is one of important days for Indonesia, is a day that commemorates one of the most important historical events, especially for the Indonesian people. The independence of the threatened Indonesian nation could be defended by heroes who sacrificed their lives against the invaders, where the incident coincided on November 10, 1945. but there are still many young people today who still do not understand the importance of their hero's struggle on that day, and consider Heroes' Day an ordinary holiday. The serious game is one of the game genres that is commonly used to provide learning about a topic by using games as learning media. By utilizing games as learning media, it will be easier for youth to understand the events of November 10 directly. The game is designed as a first-person shooter game developed using Unity with players playing the role of fighters against invaders on November 10, 1945. After playing, players will be given a series of questionnaires that contain events that occurred in the game and provide value to the game application. from the results of the questionnaire, the value obtained from the questionnaire was 69 and the value of the aspects of the game was 3.37
Web-Based Administration Applications For Motorcycle Dealers Using FAST Framework
Get PDF
Administrative management is very important in business, including the motorcycle sales business. The existence of an integrated system to handle administrative activities is absolutely necessary to increase work efficiency and tidy up the storage of related documents. In this research, the development of an administration system for motorcycle dealers will be carried out using the FAST Framework. FAST Framework was chosen because of its ability to support rapid application development. In this study, FAST Framework will be carried out in five stages, namely scope definition, problem analysis, requirements analysis, logical design and physical design for the development of motorcycle dealer administration applications, so that applications will be produced that suit user needs. The results of this study will be used to collect data on license plates, collect data on vehicle registration, collect data on motorcycle down payment, and collect data on motorcycle sales. From the results of this study, an application has been produced that will facilitate business administration and service customer data needs. The resulting application has been tested and can run well to handle the necessary business administration needs. Through the application produced by this research, consumers also no longer need to come directly to the dealer to check the status of motor vehicle registration because it can be done online