An Intelligent DMI-based Feature Selection Approach for Measuring Customer Loyalty using SVM

 The business competition among different companies has exponentially increased in recent years. To remain in business, there is a pressing priority for an increased focus on customer satisfaction that ultimately fosters customer loyalty. The customer loyalty analysis is critically important to retaining current customers and attracting more new customers. The proposed...

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Artificial Intelligence inEducation: Enhancing Learning Experiences and Personalization

 The use of Artificial intelligence (AI) for educational purposes is examined in this assignment, along with how it might improve and personalize learning. The use of AI allows for the personalization of learning paths for each student, the identification of performance gaps, and the delivery of focused interventions. The literature review focuses on how AI can...

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A Logic Petri Net Model for Dynamic Multi-Agent Game Decision-Making

 This study proposes a logical Petri net model to leverage the modeling advantages of Petri nets in handling batch processing and uncertainty in value passing and to integrate relevant game elements from multi-agent game processes for modeling multi-agent decision problems and resolving optimization issues in dynamic multi-agent game decision-making. Firstly, the attributes...

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Spatial federated learning and blockchain-based 5G communication model for hiding confidential information

 At present, the preferred method of transmitting a rapid blockchain message is to send several transactions, constituting a covert 5G communication technique. However, this approach is inadequate for processing larger quantities of sensitive data, and the potential for losing confidential information is significant. Additionally, the sender’s identity is not concealed....

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Exploring the Profound Influence of Machine Learning on Business Intelligence: A Comprehensive Review

In the dynamic landscape of data-driven decision-making, the intersection of Machine Learning (ML) and Business Intelligence (BI) has become a pivotal arena, propelling organizations toward more informed and strategic insights. The fusion of these two domains is characterized by a continuous evolution, marked by innovative trends that redefine how businesses extract value...

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An Efficient Machine Learning Prediction Method for Vehicle Detection: Data Analytics Framework

 The availability of transportation is considered a significant hallmark of a developed society. Since the evolution of the human species, the imperative to relocate from one location to another has been a fundamental requirement. At present, there exists a plethora of transportation options in Indonesia. However, most individuals favor road transportation due to its...

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Streamlining Stock Price Analysis: HadoopEcosystem for Machine Learning Models and BigData Analytics

The rapid growth of data in various industries has led to the emergence of big data analytics as a vital component for extracting valuable insights and making informed decisions. However, analyzing such massive volumes of data poses significant challenges in terms of storage, processing, and analysis. In this context, the Hadoop ecosystem has gained substantial attention due...

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Support Vector Machine for Multiclass Classification of Redundant Instances

 In recent years, support vector machine has become one of the most important classification techniques in pattern recognition, machine learning, and data mining due to its superior classification effect and solid theoretical base. However, its training time will increase dramatically as the number of samples increases, and training will become more sophisticated...

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Cognitive Approach Using SFL Theory in Capturing Tacit Knowledge in Business Intelligence

The complexity of Business Intelligence (BI) processes need to be explored in order to ensure the BI system properly treats the tacit knowledge as part of the data source in the BI framework. Therefore, a new approach to handling tacit knowledge in the BI system still needs to be developed. The library is an ideal place to gather tacit knowledge. It is a place full...

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Data Analitik dan Data Analisis serta Data Science

Four Types of Data Analytics. Sumber: Intellipaat Beberapa orang percaya bahwa Data analitik dan Data Analisis memiliki makna yang sama. Dari situ terkadang beberapa orang menggunakannya secara bergantian. Secara teknis ini tidak benar. Sebenarnya ada perbedaan yang jelas antara keduanya. Jadi mari kita bahas perbedaan yang tidak begitu jelas antara istilah analisis dan...

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Ilmu Data (Data Science) dalam Kegiatan Bisnis

Four Types of Data Science Jobs sumber: Udacity Mengapa data sangat penting? Apa yang begitu penting tentang data dan hubungannya dengan bisnis yang sehat? Seiring dengan berjalannya sebuah perusahaan, apakah dengan ketersediaan data atau tidak, sangat dapat disimpulkan bahwa data adalah dasar dari setiap perusahaan yang sukses. Selain itu, pihak manajemen level dalam...

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Tacit Knowledge for Business Intelligence Framework: A Part of Unstructured Data?

Idea to capture knowledge from different sources can be very beneficial to Business Intelligence (BI). Organizations need to collect data sources from type of structured and unstructured, including individuals' tacit knowledge in order to have the better output in data analysis. Therefore, the complexity of BI processes need to be explored in order to ensure the process...

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