Agung Trisetyarso’s research while affiliated with Multimedia Nusantara University and other places

... By combining these software tools, researchers enhanced the analysis process. they gained more profound insights into the respective fields of study, showcasing the importance of utilizing multiple software programs for comprehensive research analysis (Fatima & Quamer, 2023;nurhidayah et al., 2024;soegoto et al., 2023) this paper uses a separate exploration of literature analysis methodologies: evaluation of performance, scientific mapping and analysis of networks (Donthu et al., 2021). the research method is summarized in Figure 1. ...

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Mapping research landscape of emerging technology in the accounting field: a bibliometric analysis

... Moving to practical implementations, Yulianti et al. (2023) improve ensemble classifiers using a hybrid quantum annealing method, and Li et al. (2023) introduce an innovative quantum approach to k-fold cross-validation, simplifying classification tasks. These developments highlight the impact of quantum computing in improving traditional machine learning techniques. ...

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Machine Learning Applications of Quantum Computing: A Review

... The authors compared four distance metrics, including the Euclidean, Manhattan, Chebyshev, and Canberra distances, in the clustering method for ensemble generation, and evaluated them based on accuracy [8]. The Canberra distance consistently achieved better results than the others, which motivates our work to explore its application in classification tasks. ...

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An accuracy analysis of classical and quantum-enhanced K-nearest neighbor algorithm using Canberra distance metric

... Both annotation and parameter tweaking can be automated. The YOLOv3-ResNet18 system is developed in [43] for 4 fish species detection and classification on the private dataset. Comparative analysis with SSD-VGG and Huawei ExeML models demonstrates the superior performance of YOLOv3-ResNet18, achieving an accuracy of 98.45%. ...

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Automatic Estuarine Fish Species Classification System Based on Deep Learning Techniques

... Subsequently, the research was extended by creating an integration-based model (I-BM) framework for MBT. The I-BM framework employed 8 variables: function, interface, structure, performance, requirement, documentation, positive, and negative to predict the accuracy level of its fault output using machine learning approaches (Zulkifli et al., 2023). Furthermore, Ali et al. (2023) conducted research on defect prediction in software using machine learning. ...

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Multi-algorithm for predicting the level accuracy of fault output in software

... Más del 70% de los clientes demandan productos y servicios digitales innovadores, mientras que la industria aún no está preparada para esta era. Esto exige repensar los indicadores clave de desempeño (KPIs), ya que, para triunfar en este nuevo entorno, los bancos deben centrarse en las opiniones de los usuarios, la imagen y la estructura financiera de la tecnología [3]. ...

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Revisión Sistemática sobre Big Data en Finanzas: Satisfacción y Lealtad

... For example, in a comprehensive review, Afriliana & Ramadhan (2022) discussed the trends of using robotic process automation technology for digital automation. Similarly, Marcel et al. (2023) proposed an extensive framework for the digital transformation of organizations for their business sustainability and to gain a competitive advantage in the market. Similarly, Adityawan et al. (2023) considered the case study of using digitization in the Islamic banking sector in Indonesia to get a competitive advantage. ...

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Assessing the Implementation and Performance of Automated Trading Software with Non-Biased Human Decisions in the Derivatives Market: Evidence from Thailand

... Numerous research works have employed algorithms to forecast the precision of defects associated with the expected software fault output. One notable study undertaken by Zulkifli et al., (2022), developed a modelbased test (MBT) using 5 variables, including performance, initialization, data structures, incorrect or missing functions, and external database access, with the neural network algorithm. Subsequently, the research was extended by creating an integration-based model (I-BM) framework for MBT. ...

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Multi-algorithm for predicting the level accuracy of fault output in software

... In the Metaverse, individuals can engage in virtual meetings where body language and eye contact can be used to convey emotions and intentions, enhancing communication and collaboration. By leveraging the immersive nature of the Metaverse, telecommuting experiences can be significantly improved, allowing coworkers to connect and collaborate seamlessly from diverse perspectives, regardless of physical distance [28][29][30]. ...

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Exploring Current Technologies, Applications, and Challenges in the Metaverse: A Comprehensive Survey

... Existen diversos softwares en el mercado que contemplan la inteligencia de negocios para extraer, transformar y cargar los datos (proceso ETL) permitiendo visualizar y analizar la información tales como: Microsoft Power BI, Tableau, Oracle Business Intelligence, Pentaho BI, IBM Cognos, Sap Business Intelligence, Looker, Qlik Sense y Sisense (Yanfi et al., 2022;García Pérez, 2020). Es posible crear dashboards (tableros de control) utilizando estos softwares, los cuales son herramientas visuales que permiten monitorear y analizar métricas clave de manera clara y en tiempo real, facilitando aún más la toma de decisiones empresariales que no solo facilitan la visualización de información, sino que también permiten tomar medidas correctivas y preventivas de manera oportuna. ...

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Integración de Inteligencia de negocios (BI) y herramientas psicológicas para la salud mental en el ámbito organizacional: Integration of Business Intelligence (BI) and psychological tools for mental health in the organizational context