Poverty is considered a serious global issue that must be immediately eradicated by Sustainable Development Goals (SDGs) 1, namely ending poverty anywhere and in any form. As a developing country, poverty is a complex...
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Indonesia has entered a period of demographic bonus. Human resources must be optimized. The number of children who do not in employment, education or training (NEET) in each province needs attention. Several factors t...
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Efficient communication plays a pivotal role in the success of university community service programs. This study highlights the innovative approach taken by the University of Riau to enhance communication within their...
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It can be argued that the Convolutional Neural Network (CNN) used in this research is an efficient algorithm for classifying images based on the end prediction of the path taken. In every plot that is made, there is a...
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Gurami is a native fish from Indonesian waters that is much-loved by Indonesian people for daily food consumption. The gurami inhabits still waters such as swamps, lakes, and ponds. Besides that, carp cannot live in a...
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Business rules are essential for organizational decision-making, shaping the functional requirements of information systems. These rules establish constraints within business processes, influencing decisions like prod...
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ISBN:
(数字)9798331533243
ISBN:
(纸本)9798331533250
Business rules are essential for organizational decision-making, shaping the functional requirements of information systems. These rules establish constraints within business processes, influencing decisions like product pricing strategies or supplier compliance evaluations. Integrating business rules into information systems ensures accurate, consistent decisions aligned with organizational objectives. The Decision Model and Notation (DMN) provides a standardized way to model decision logic, capture dependencies, and organize related data elements. DMN enhances the Business Process Model and Notation (BPMN) by incorporating decision-making logic into business process models, making them accessible to both business and technical stakeholders. While the Unified Modeling Language (UML) and BPMN are widely used in system modeling, DMN's practical application for decision modeling remains underexplored. This paper presents a practical implementation of DMN, focusing on its integration with BPMN for a comprehensive approach to information system design. Using a case study, we demonstrate how DMN effectively represents decision logic, showcasing benefits such as improved clarity, flexibility, and reusability. In evaluating different scenarios, Scenario S1 achieved the highest efficiency improvement of 19%, while Scenario S3 showed the least with only a 5% gain. These findings indicate that the adjustments in Scenario S1 can significantly enhance the performance of the Publication Incentive Information system, leading to recommendations for decision-makers to optimize evaluation criteria and processes.
Learning to write in children requires the child's habit of using a pencil to write on paper. The manual method has drawbacks such as the use of a lot of paper when children have to study harder to keep repeating ...
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Efficient communication plays a pivotal role in the success of university community service programs. This study highlights the innovative approach taken by the University of Riau to enhance communication within their...
Efficient communication plays a pivotal role in the success of university community service programs. This study highlights the innovative approach taken by the University of Riau to enhance communication within their community service initiative through the implementation of Kukerti, a cutting-edge chatbot system. Developed specifically for Bahasa Indonesia-speaking users, Kukerti utilizes advanced fuzzy string-matching algorithms to process user inputs and generate relevant responses. In this study, we delve into the deployment and impact of the Kukerti chatbot within the University of Riau’s community service program. We explore its functionality in addressing the common challenge of delayed responses from web administrators, which had previously hindered efficient information retrieval for students and participants. Our research aims to explore how does the implementation of the Kukerti chatbot system with advanced fuzzy string-matching algorithms impact the efficiency of communication and information retrieval within the University of Riau’s community service program. The result shows the implementation of fuzzy string-matching algorithms improves the communication process and the evaluation of the Kukerti chatbot showed that the implementation of fuzzy string-matching has an accuracy rate of 93.33% in providing the answers. By exploring the fuzzy string-matching implementation in the Kukerti chatbot, it is expected to provide further understanding regarding the implementation and encourage other chatbot developers to use it.
Widyaiswara is required to show the best performance to fulfill his duties and obligations. Therefore, it is very important to measure the performance of the Widyaiswara, so that it can be used as evaluation material ...
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It can be argued that the Convolutional Neural Network (CNN) used in this research is an efficient algorithm for classifying images based on the end prediction of the path taken. In every plot that is made, there is a...
It can be argued that the Convolutional Neural Network (CNN) used in this research is an efficient algorithm for classifying images based on the end prediction of the path taken. In every plot that is made, there is a similar process for achieving a prediction of the final result. The implementation for each of these procedures follows the steps that are summarized into a flow of analysis stages that can help to develop the application of an algorithm. The initial stage is to take the handwriting from the user which is then pre-processed the image, to eliminate existing noise, and sharpen the contrast, so that the image can be seen clearly. Images will be processed and analyzed using the Convolutional Neural Network model, training will be carried out, with an average training of a dataset of 100 epochs or about 7 to 10 minutes, and labeling on the trained dataset. The accuracy of the training reached 98.89%, as a proportion of the different characteristics of the handwriting sample.
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