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Recommendation System Journalist for Getting Top News Based on Twitter Data

Recommendation System Journalist for Getting Top News Based ...

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2019 International Conference of science and Information Technology in Smart Administration, ICSINTeSA 2019

作者： Girsang, Abba Suganda Isa, Sani Muhamad Harvy, Ikrar Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

One application that can be utilized in finding the latest news is by utilizing the development of information and communication technology such as seeing the delivery of public information through social media such as twitter. This study implements the system which is able to get the trending or top news based on twitter data. This information will connect to the journalist via mobile application. It helps journalists to get the potential news to be reported in their media. The application will group each tweets into various themes based on the cosine similarity. The tweets which are more the certain threshold, can be indicated as the top news. The top news is then classified into one category news by using SVM algorithm. The training data becomes from the source data of one media news. The specific topic of this result will ease to order the journalist cover this top news. The system can be implemented well. © Published under licence by IOP Publishing Ltd.

关键词： Social networking (online)

来源：评论

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Big Data Security Approach in Cloud: Review 3

Big Data Security Approach in Cloud: Review

引用

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

作者： Damayanti, Finka Ria Elmizan, Kemal Anshari Alfredo, Yoel Frans Agam, Zidni Nurrobi Wibowo, Antoni Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

In big data era, data may be in the form of structured, unstructured and semi-structured. They become an asset for companies that contain important insights and support in decision-making processes. Big data is one of technologies that used by many organizations for managing store data and data analysis. Therefore, storage management is one of important processes in big data management to ensure that data are stored correctly, safely and easily to be accessed. Despite having many advantages, big data technology still has several issues on storage management, especially if we relate between big data and cloud computing, such as data security which is very important. In this paper, we reviewed the previous works for data security in storage management in big data technology and provide a suggestion to answer the challenge of data security. © 2018 IEEE.

关键词： Big data

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Analysis of Enterprise Architecture Research Trends for Higher Education Institutions Using Systematic Literature Review and Vos Viewer

Analysis of Enterprise Architecture Research Trends for High...

引用

2023 International Conference on Informatics Engineering, science and Technology, INCITEST 2023

作者： Soegoto, Yudistira Prabowo, Harjanto Spits Warnars, Harco L H Trisetyarso, Agung Bina Nusantara University Binus Graduate Program Doctor Computer Science School of Computer Science Computer Science Departemen Jakarta11480 Indonesia Bina Nusantara University School of Computer Sicence Mathematics Departement Jakarta11480 Indonesia

ISBN: (纸本)9798350317862

Enterprise Architecture Framework (EAF) is a commonly used framework and the best solution for addressing and defining the transformation that needs to be built to support business operations. To be able to make the transition quickly, many higher education institutions (HEIs) are starting to adopt EAF. This research aims to help the evolution and transpiration of enterprise architecture research in higher education. This research uses a systematic literature review (SLR) research method which includes several steps, namely identifying research questions, identifying research sources, using keywords to complete the data discovery process, disseminating data, and analyzing the results to answer research questions. The data used comes from digital libraries, especially Emerald Insight, IEEE Xplore Digital Library, and science Direct. Data taken from 2019 to 2023 in RIS format will then be analyzed and visualized using VosViewer. The results of this research are to find the growth of research publications over five years, find research trends on enterprise architecture frameworks, identify relationships between scientific concepts, and determine the knowledge network of enterprise architecture frameworks based on keywords. © 2023 IEEE.

关键词： Digital libraries

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A review of traffic violation detection technology in reporting mechanism 2

A review of traffic violation detection technology in report...

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2nd International Conference on Biospheric Harmony Advanced Research, ICOBAR 2020

作者： Alaydrusl, A. Putra, W.K. Nugroho, Y. Muhammad Surantha, N. Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Traffic Violation Detection system using radio frequency identification (RFID) has been applied to detect vehicles with limited power sources through RFID Tag. Camera sensors are also applied to identify a vehicle and its plate number through image and video processing known as computer vision. On the other hand, vehicular ad hoc network (VANET) to gain information about location, speed, and so on through the vehicle-to-vehicle (V2V) connection. Lastly, the internet-of-things that is backed-up by cloud computing helps to store various information from each of these technologies and process them to get results. Many researchers have proposed and developed algorithms or technology with astonishing experimental results of them. However, there has been no review of the integration and reporting mechanism that correlates them. There has also been no review about how to connect the information to the authority and violator. Therefore, the review was made to explain each technology's method with their experiment's results and issues. Moreover, the future challenge also had been given to further research. © Published under licence by IOP Publishing Ltd.

关键词： Vehicles

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Object Driven Fuzzy Decision Model for Evaluating the Cryptocurrency's Performance 11

Object Driven Fuzzy Decision Model for Evaluating the Crypto...

引用

11th International Conference on ICT for Smart Society, ICISS 2024

作者： Utama, Ditdit Nugeraha Binus Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350389654

The assessment of cryptocurrency performance has been subject to criticism due to the lack of a standardized approach, leaving the evaluation process without clear guidance. In this research, an innovative object-driven decision model based on fuzzy logic (OFDM) conception was developed to systematically analyze cryptocurrency performance. Object-oriented operated as the main method in analyzing and designing the model. In this context, the model elements deeply observed and functioned to become fundamental thinking for constructing the model. Then, fuzzy logic with curve membership function form was also used as the primary method to avoid the bias value of three key parameters;trend line (and then used to see the slope distance), price consistency, and transaction volume consistency. The constructed model is a novel decision model that was successfully constructed for assessing the determined cryptocurrency performance. Utilizing six months of real data from three major cryptocurrencies (Bitcoin, Ethereum, and Dogecoin), the model conclusively demonstrates that Bitcoin exhibits the strongest performance, scoring 36.39 performance points. © 2024 IEEE.

关键词： Fuzzy logic

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Easy Data Augmentation for Handling Imbalanced Data in Fake News Detection 1

Easy Data Augmentation for Handling Imbalanced Data in Fake ...

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1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Pradana, Rilo Chandra Joddy, Setiawan Girsang, Abba Suganda Binus Graduate Program-Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350360554

Detecting fake news in the digital era is challenging due to the proliferation of misinformation. One of the crucial is-sues in this domain is the inherent class imbalance, where genuine news articles significantly outnumber fake ones. This imbalance severely hampers the performance of machine and deep learning models in accurately identifying fake news. Consequently, there is a compelling need to address this problem effectively. In this study, we delve into fake news detection and tackle the critical issue of imbalanced data. We investigate the application of Easy Data Augmentation (EDA) techniques, including back-translation, random insertion, random deletion, and random swap to mitigate the adverse effects of imbalanced data. This study focuses on employing these techniques in conjunction with a deep learning framework, specifically a Bidirectional Long Short-Term Memory (BiLSTM) architecture. The results of the EDA techniques will be systematically compared to see their effectiveness and their impacts on model performance. This study reveals that various EDA techniques, when coupled with a BiLSTM architecture, yield significant improvements in fake news detection. Among the experiments, it shows that Random Insertion, with an impressive accuracy rate of 81.68%, a precision score of 89.38%, and an F1-Score of 87.77% emerges as the most promising technique. The study also highlights the exceptional potential of Back-translation stands out with an 87.16% recall performance. © 2023 IEEE.

关键词： Long short-term memory

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Critical Success Factor of Information Technology Implementation in Supply Chain Management: Literature Review 5

Critical Success Factor of Information Technology Implementa...

引用

5th International Conference on Information Technology, computer and Electrical Engineering, ICITACEE 2018

作者： Fernando, Erick Surjandy Warnars, Harco Leslie Hendric Spits Meyliana Kosala, Raymond Abdurachman, Edi Computer Science Department BINUS Graduate Program - Doctor of Computer Science Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538655276

The main objective of this research is to explore the success factors of implementation information technology (IT) in supply chain management. The method used is a literature review with meta-analysis approach, meta-analysis used by using keywords that describe the search. The results of this study found 56 success factors, after further analysis found 21 success factors are very influential from the implementation IT, among others: Efficient, Integration, Cost, Effectiveness, Communication, Ability, Timeliness, Accurate, Accurate, Performance, Coordination, Flexible, Automation, Quality, Transparent, Real-Time, Responsiveness, Trust, Speed, Completeness, Relationships, Suitability. This factor gives the company the desire to implement IT in the supply chain. The application of IT has a positive influence on all supply chain activities so it can improve the processes that occur within the company from purchasing raw materials, production processes, logistics, customer service. All this gives the opportunity for a company to compete globally with others. © 2018 IEEE.

关键词： Supply chain management

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The Fuzzy-AHP Decision Model for Managing Smart City: An Object-Oriented Model for Bibliometric Based Literature Review 11

The Fuzzy-AHP Decision Model for Managing Smart City: An Obj...

引用

11th International Conference on ICT for Smart Society, ICISS 2024

作者： Utama, Ditdit Nugeraha Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350389654

Operating a smart city is intricate and requires comprehensive management. Implementing a decision model is one effective and efficient method to address this complexity. This study seeks to systematically review articles to see the trends in the utilization of fuzzy logic methods and their combinations, particularly in a decision model that supports smart city operations. Through four stages, the study not only presents the bibliometric-based review findings to address specific inquiries but also produces an object-oriented model for review purposes. Based on 131 articles, the research trend indicates a linear growth in studies focusing on smart cities and decision models, with a particular emphasis on incorporating fuzzy logic models. Additionally, according to 9 deep-reviewed articles, the analytic hierarchy process (AHP) emerges as a popular method often combined with the fuzzy logic method. As well, the object-oriented model for review purposes is developed with 19 interrelated objects. It is the main contribution of the study. © 2024 IEEE.

关键词： Smart city

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Neural controller design for a class of nonlinear systems with time-varying delay: A bibliometric analysis-based short literature review

Neural controller design for a class of nonlinear systems wi...

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2023 International Conference on computer science, Information Technology and Engineering, ICCoSITE 2023

作者： Wijaya, Santo Gaol, Ford Lumban Wibowo, Antoni Zarlis, Muhammad Bina Nusantara University BINUS Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Information System Management Information System Management Department Jakarta11480 Indonesia

ISBN: (纸本)9798350320954

Real-world practical systems inherently exhibit non-linearities in their dynamics. Also, it is known that a time-varying delay exists in the system state or input-output. Combined, it affects the stability of the closed-loop system. It also increases the complexity of the controller design. In-depth controller design research on the class of Nonlinear Systems with Time-Varying Delay (NSTVD) has been the focus of the control community for many years. However, there is a lack of Systematic Literature Review (SLR) and classifications of the papers on this topic. This paper aims to review controller design utilizing a neural network model for the class of NSTVD systems. The study employs Kitchenham's SLR method to gather, analyze and synthesize published papers from reliable databases between 2017 and 2021. The bibliometric analysis for the selected 38 papers reveals the prolific authors, countries, affiliations, publishers, co-authorship network, co-occurrences of keywords, and ten most-cited papers. Finally, this paper developed a conceptual map outlining six multi-layered findings: the addressed problem, control design method, nonlinear system properties, time-varying delay properties, system constraint properties, and actuator limit properties. A brief qualitative analysis of the ten most-cited papers is performed based on the map. The findings highlighted that the proposed methods have shown encouraging results in the simulation domain and can be used as a source of inspiration for future studies and implementation of the neural controller design of the NSTVD system. © 2023 IEEE.

关键词： Nonlinear systems

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Virality Prediction on Twitter Using Combined CNN and BERT Models 4

Virality Prediction on Twitter Using Combined CNN and BERT M...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Benedecas, Hilarius Ryan Auxilio Girsang, Abba Suganda Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798331506490

Nowadays, social media serves as a platform for sharing and receiving information. One indicator of the importance of information is its virality. Virality is an interesting topic in the world of Natural Language Processing (NLP), including the prediction of virality and identifying features that influence it. Research in this area has utilized Bidirectional Encoder Representations from Transformers (BERT) models and yielded promising results. Previous studies aimed to predict virality based on specific features. This research aims to predict virality by combining the abilities of Convolutional Neural Network (CNN) and BERT models. The BERT model transforms textual data into numerical and adds new features, while the CNN model excels in numerical classification. Data for this study is sourced from Twitter and in Indonesian language. The proposed model demonstrates improvements compared to the model from previous research. Specifically, it shows a 7.1% increase in precision, a 9.9% increase in recall, a 3.8% increase in accuracy, and an 8.1% increase in F1-Score compared to the previous model. These findings contribute to future research on similar topics, particularly in leveraging multiple models for prediction tasks. Overall, the study provides insights into effectively utilizing the strengths of various models and combining them in prediction tasks. © 2024 IEEE.

关键词： Prediction models

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