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Implementing and Improving a method for non-invasive elicitation of probabilities for bayesian networks 07

Implementing and Improving a method for non-invasive elicita...

International Conference on computer systems and Technologies and Workshop for PhD Students in Computing, CompSysTech '07

作者： De Jongh, Martinus Druzdzel, Marek Rothkrantz, Leon Faculty of Electrical Engineering Mathematics and Computer Science Man-Machine Interaction Group Delft University of Technology Delft Netherlands Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA United States

ISBN: (纸本)9789549641509

Knowledge elicitation is difficult for expert systems that are based on probability theory. The elicitation of probabilities for a probabilistic model requires a lot of time and interaction between the knowledge engineer and the expert. Druzdzel and van der Gaag [5] have proposed a theoretical framework that would allow the use of multiple types of probabilistic information for elicitation of Bayesian networks. This framework has been used as a starting point for the implementation of a non-invasive elication method. © 2007 ACM.

关键词： Linear programming

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Analyzing the Effectiveness of Smartphone Applications on Disease Management and Healthcare systems

Analyzing the Effectiveness of Smartphone Applications on Di...

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International Conference on Application of information and Communication Technologies (AICT)

作者： Rabei Raad Ali Wisam Subhi Al-Dayyeni Christy Atika Sari Eko Hari Rachmawanto Candra Irawan Omar M. Jihad Department of Computer Engineering Technology Northern Technical University Mosul Iraq School of Information Technologies and Engineering ADA University Baku Azerbaijan Study Program in Informatics Engineering Faculty of Computer Science University of Dian Nuswantoro Semarang Indonesia Study Program in Information Systems Faculty of Computer Science University of Dian Nuswantoro Semarang Indonesia

ISBN: (数字)9798350387537

ISBN: (纸本)9798350387544

In today’s complex global environments, it is highly challenging to achieve effective healthcare management. The critical challenges faced by healthcare management are being met by the revolution of m-health where mobile cloud computing plays a major role. The taxonomy of mobile computing comprises operational aspects, end-user issues, and service quality and mobility management. The use of smartphone technologies and applications has become a highly significant approach to improving healthcare management. Mobile health services such as mobile pathology, mobile neurosurgery, cancer treatment, and behavioral/psychological disorders are gaining significance where smartphone applications are being used. Portability, flexibility, and convenience are major characteristics of mobile computing that have helped patients and doctors to develop better relationships through coordination and communication. The relationship between smartphone technologies and applications and healthcare management can be understood in several broad aspects. This article aims to analyze the current and future implications of these technologies on healthcare and disease management systems.

关键词： Pathology Cloud computing Taxonomy Cancer treatment Medical services Benchmark testing Neurosurgery information and communication technology Mobile computing Diseases

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Placement of information systems as a strategic tool for achieving company objectives 7

Placement of information systems as a strategic tool for ach...

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7th information systems International Conference, ISICO 2023

作者： Sardjono, Wahyu Perdana, Widhilaga Gia Cholidin, Achmad Salim, Guntur Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Post Graduate Program of Management Science State University of Jakarta Jl. R.Mangun Muka Raya No.11 Jakarta Timur Jakarta13220 Indonesia Law Study Program Faculty of Law University of Muhammadiyah Jakarta Indonesia Post Graduate Program Faculty of Economic Science University of Trisakti Jl. Kyai Tapa No. 1 Grogol Jakarta11440 Indonesia

The information system is a strategic tool for the goals but is considered not optimal because there are indications that long-term target strategies have not been achieved. it is necessary to identify the factors that influence this success so that a model can be built that describes the achievement of the company's strategic objectives. The research was conducted with a quantitative approach through an analysis of data using factor analysis and regression analysis. The results of the study show three factors that influence strategic goals in companies, namely Leadership & Organizational, Goals Visualization, and Enterprise-wide Awareness. © 2023 The Authors. Published by Elsevier B.V.

关键词： Factor analysis

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Implementation of AI-Based Support Vector Machine Algorithm for Fraud Detection in Digital Payment systems

Implementation of AI-Based Support Vector Machine Algorithm ...

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International Seminar on Research of information Technology and Intelligent systems (ISRITI)

作者： Edy Prayitno Rikie Kartadie Uning Lestari Munengsih Sari Bunga Accounting Information Systems Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Computer Engineering Study Program Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Informatics Study Program Faculty of Science and Information Technology Universitas Akprind Indonesia Yogyakarta Indonesia Department of Computer Engineering Smart City Information Systems Politeknik Negeri Indramayu Indramayu Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

The increasing use of digital payment systems has led to a rise in fraudulent activities, presenting a significant challenge in ensuring secure transactions. This research focuses on implementing the Support Vector Machine (SVM) algorithm with a Radial Basis Function (RBF) kernel to detect fraud in digital payment systems. One of the main challenges addressed in this study is the severe class imbalance in the dataset, where fraudulent transactions account for only 0.17% of total transactions. To overcome this, the SMOTE (Synthetic Minority Over-sampling Technique) method was applied to balance the dataset, allowing the model to better recognize fraudulent patterns. The results indicate that the SVM model achieved an accuracy of 99.93%, with a precision of 86.23% and a recall of 75.51%. These results demonstrate that SVM, combined with SMOTE and RBF kernel, is highly effective in detecting fraudulent transactions while minimizing false positives. This research provides a strong foundation for improving fraud detection models in the context of digital payment systems, offering enhanced security and trust for users. Further research could explore hybrid models and real-time data analysis to improve performance.

关键词： Support vector machines Seminars Adaptation models Accuracy Data models Real-time systems Fraud Security Kernel Intelligent systems

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The Trigger Factors and Constraints on e-Supply Chain Processes: A Systematic Literature Review 3

The Trigger Factors and Constraints on e-Supply Chain Proces...

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3rd International Conference on information Management and Technology, ICIMTech 2018

作者： Maniah Meyliana Hidayanto, Achmad Nizar Prabowo, Harjanto Gaol, Ford Lumban Computer Science Department Bina Nusantara University Major of Informatics Management Jakarta Bandung11480 Indonesia Information Systems Department Bina Nusantara University School of Information Systems Jakarta Indonesia11480 Indonesia Faculty of Computer Science University of Indonesia Depok16424 Indonesia Management Department Bina Nusantara University BINUS Business School Undergraduate Program Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The development of information technology will certainly have a major influence on all aspects of life, not least for companies engaged in the supply chain. The role of information technology and electronic networks in running a supply chain is called the Electronic Supply Chain (e-Supply Chain). The main point of this research is to conduct a literature review to find the trigger factors and constraints in the e-supply chain. This research uses the Systematic Literature Review methodology to collect selected research articles. The steps in defining the selected article use PRISMA. Keywords used for article search are ('Trigger' OR 'Driving') AND 'Factors' AND 'Constraints' AND ('Supply Chain' OR 'SC') AND (' electronics supply chain' OR 'e-supply chain') AND 'Processes'. Source of data used includes: Elsevier, ACM Digital Library, Emerald Insight, IEEE Explore, Inder science publisher, and Springer. Based on the literature review that was carried out, the resulting trigger factors in the e-supply chain, including: Integrated supply chain system, IT Support, Service quality;while the constraints include: A supply chain network cyber attack, Manufacturing, storage or distribution problems, Operational, economic, environmental and social factors, Restrictive government regulations, Costs and logistics performance, cost of raw materials, Post-harvest waste, Global / digital markets, product life cycles, consumer demand, Logistics strategy, Global competitiveness, Internationalization of markets and climate change. © 2018 IEEE.

关键词： Supply chains

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Bloom-epistemic and sentiment analysis hierarchical classification in course discussion forums

arXiv

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arXiv 2024年

作者： Toba, Hapnes Hernita, Yolanda Trixie Ayub, Mewati Wijanto, Maresha Caroline Master of Computer Science Study Program Faculty of Information Technology Maranatha Christian University Bandung Indonesia Bachelor of Informatics Study Program Faculty of Information Technology Maranatha Christian University Bandung Indonesia

Online discussion forums are widely used for active textual interaction between lecturers and students, and to see how the students have progressed in a learning process. The objective of this study is to compare appropriate machine-learning models to assess sentiments and Bloom's epistemic taxonomy based on textual comments in educational discussion forums. The proposed method is called the hierarchical approach of Bloom-Epistemic and Sentiment Analysis (BE-Sent). The research methodology consists of three main steps. The first step is the data collection from the internal discussion forum and YouTube comments of a Web programming channel. The next step is text preprocessing to annotate the text and clear unimportant words. Furthermore, with the text dataset that has been successfully cleaned, sentiment analysis and epistemic categorization will be done in each sentence of the text. Sentiment analysis is divided into three categories: positive, negative, and neutral. Bloom's epistemic is divided into six categories: remembering, understanding, applying, analyzing, evaluating, and creating. This research has succeeded in producing a course learning subsystem that assesses opinions based on text reviews of discussion forums according to the category of sentiment and epistemic analysis. © 2024, CC BY-SA.

关键词： Sentiment analysis

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A Literature Review: Drug Supply Chain and Neural Networks 6

A Literature Review: Drug Supply Chain and Neural Networks

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6th International Conference on information Technology, information systems and Electrical Engineering, ICITISEE 2022

作者： Emmanuel, Gunadi Meyliana Hidayanto, Achmad Nizar Prabowo, Harjanto Bina Nusantara University Computer Science Jakarta Indonesia Fakultas Sains Dan Teknologi Unika Katolik Musi Charitas Palembang Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia Management Departement BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798350399615

The drug supply chain is an important variable that will be asked when there is a shortage of drugs. The distribution and storage of drugs require accurate predictions to support the drug supply chain. Many methods have been studied to obtain a high level of prediction accuracy. One of the methods used is an artificial neural network to recognize the pattern of drug demand. It is important to find breakthroughs in artificial neural network technology to anticipate drug shortages. This study seeks to identify and find challenges from previous research in drug supply management and drug demand prediction by utilizing neural networks over the past five years. From the seven sources used, 34 articles were selected based on inclusion criteria and keyword searches according to Kitchenham's systematic review methodology. The discussion areas of the selected articles are 29% in the Logistics and Inventory area, 20% Risk - Resilience, and 18% for Drug supply chain planning which is a description of the research development area. Integrated development provides room for the use of neural networks in these three correlated areas. The model for implementing neural networks in maintaining the continuity of drug shortages is always associated with policies adopted by all drug supply chain stakeholders to anticipate drug shortages. © 2022 IEEE.

关键词： artificial neural network drugs supply chains pharmaceutical

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Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem 5

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

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5th International Conference on Cybernetics and Intelligent systems, ICORIS 2023

作者： Anditta, Mietha Amartya, Natashya Warnars, Laurens Spits Warnars, Harco Leslie Hendric Spits Ramadhan, Arief Siswanto, Teddy Mantoro, Teddy Noordin, Nurulhuda Bina Nusantara University School of Computer Science Computer Science Departement Jakarta11530 Indonesia Bina Nusantara University School of Information Systems Information Systems Departement Jakarta11530 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Departement Jakarta11530 Indonesia Telkom University Pjj Informatika Bandung40257 Indonesia Trisakti University Information Systems Department Jakarta11440 Indonesia Sampoerna University Faculty of Engineering and Technology Jakarta12760 Indonesia Universiti Teknologi Mara School of Computing Sciences College of Computing Informatics and Mathematics Selangor Malaysia

ISBN: (纸本)9798350369489

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset. © 2023 IEEE.

关键词： Dynamic programming

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New Media as a Tools to Improve Creative Thinking: A Systematic Literature Review

New Media as a Tools to Improve Creative Thinking: A Systema...

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International Conference on information Technology, information systems and Electrical Engineering (ICITISEE)

作者： Hellik Hermawan Fajar Mahardika Irma Darmayanti R. Bagus Bambang Sumantri Dhanar Intan Surya Saputra Afrig Aminuddin Department of Informatics Faculty of Computer Science Universitas Amikom Purwokerto Banyumas Jawa Tengah Indonesia Computer Technology Study Program Faculty of Science and Technology Institut Teknologi dan Sains Nahdlatul Ulama Pekalongan Indonesia Department of Information technology Faculty of Computer Science Universitas Amikom Purwokerto Banyumas Jawa Tengah Indonesia Information Systems Study Program Faculty Of Science and Technology Universitas Harapan Bangsa Indonesia Faculty of Computer Science Universitas Amikom Yogyakarta Sleman Indonesia

This systematic literature review (SLR) study aims to analyze the role of New Media as a Tool to Improve Creative Thinking, with relevant articles from 2018 to 2023 taken from reputable international journals. It uses three research questions (RQ) to explore New Media's relevance in stimulating creativity. The results indicate that interactive platforms such as social media and online collaboration tools positively influence creative thinking skills. Interaction through New Media allows individuals to share ideas, discuss, and be exposed to various points of view, all of which stimulate creative thinking. In addition, New Media also facilitates the creative process of solving problems and generating original ideas. The immersive experiences offered by this technology can enhance the exploration of ideas and increase the ability to think out-of-the-box. While New Media offers great potential to enhance creativity, there are also potential risks, such as false information, media addiction, and privacy concerns. Therefore, awareness of the wise use of New Media needs to be increased, especially in education and everyday life. Overall, this literature review provides in-depth insight into the role of New Media in enhancing creative thinking skills and driving innovation. With the right approach, New Media can be an effective tool in stimulating creative thinking and encouraging the creation of original ideas beneficial for future social and technological developments.

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Prediction of Consumer Purchase Intention on Green Product

Prediction of Consumer Purchase Intention on Green Product

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2021 International Seminar on Application for Technology of information and Communication, iSemantic 2021

作者： Hariyadi, Guruh Taufan Purwanto Isnanto, R Rizal Wibowo, Adi Warsito, Budi Universitas Diponegoro Doctoral Program of Information Systems Semarang Indonesia Universitas Diponegoro Faculty of Engineering Department of Chemical Engineering Semarang Indonesia Universitas Diponegoro Faculty of Engineerig Department of Computer Engineering Semarang Indonesia Universitas Diponegoro Faculty of Science and Mathematics Departement of Informatics Semarang Indonesia

ISBN: (纸本)9781665428040

Education to the public on green products has been widely carried out. Consumers who buy green products can be profiled by segmenting green consumers. In green marketing, consumer education on sustainable consumption is increasingly needed in recent years due to the problem of environmental pollution which poses a serious threat to the world population. Concern for the environment is an important topic in most countries, and individuals also study environmental issues. Individuals or groups of individuals who are 'ecologically aware' are also referred to as 'green consumers.' Such consumers are considered to have more concern for the environment. This study examined the predictions on the effect of the Green Perceived Value variables consisting of functional, conditional, and social values on the purchase intention of green consumers. It also tested the comparisons with other classification models. The models used in this research were Random Forest, Decision Tree, and Neural Network.. © 2021 IEEE.

关键词： Consumer behavior

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