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Sentiment Analysis on the Construction of the Jakarta-Bandung High-Speed Train on Twitter Social Media Using Recurrent Neural Networks Method

Titan Kinan Salaatsa, Yuliant Sibaroni

During the construction of the Jakarta-Bandung high-speed train, many Indonesian people gave their responses to the public. The answers were also varied, with some giving positive and negative reactions. The purpose of this study is to analyze the sentime... see more

high-speed train | sentiment analysis | recurrent neural networks | twitter

Digital Zone: Jurnal Teknologi Informasi dan Komunikasi , 2048

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Bayesian networks approach on intelligent system design for the diagnosis of heat exchanger10.22441/sinergi.2022.2.001

Dedik Romahadi,Fajar Anggara,Rikko Putra Youlia,Hifdzul Luthfan Habibullah,Hui Xiong

The heat exchanger highly influences the series of cooling processes. Therefore, it is required to have maximum performance. Some of the factors causing a decrease in its performance are increased pressure drop in the Plate Heat Exchanger (PHE), decreased... see more

Bayesian Networks | Intelligent system | Plate Heat Exchanger | Pressure drops |

Jurnal Ilmiah SINERGI , 2022

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Descriptive Analysis and ANOVA Test with File Sending on Computer Networks Attacked with Rogue's Dynamic Host Configuration Protocol (DHCP)

Hero Wintolo,Yuliani Indrianingsih,Wahyu Hamdani,Syafrudin Abdie

The requirement for a computer that is physically connected to a computer network to be able to access existing resources on a computer network in the form of an IP address obtained statically or dynamically. On a static IP address, there are not many pro... see more

Descriptive Analysis | Nova Test | Networks Attacked | DHCP Rogue

Jurnal Teknik Elektro Komputer dan Informatika , 2023

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Predicting extreme events in the stock market using generative adversarial networks

(1) Badre Labiad (Equipe AMIPS, Ecole Mohammadia d’Ingénieurs, Mohammed V University in Rabat, Morocco) (2) Abdelaziz Berrado (Equipe AMIPS, Ecole Mohammadia d’Ingénieurs, Mohammed V University in Rabat, Morocco) (3) Loubna Benabbou (Université du Québec à Rimouski (UQAR), Campus de Lévis, Canada)

Accurately predicting extreme stock market fluctuations at the right time will allow traders and investors to make better-informed investment decisions and practice more efficient financial risk management. However, extreme stock market events are particu... see more

Extreme events prediction | Time series generation | Stock markets simulation | Generative adversarial networks | Long short-term memory

International Journal of Advances in Intelligent Informatics , 2023

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Predicting extreme events in the stock market using generative adversarial networks

Extreme events prediction | Time series generation | Stock markets simulation | Generative adversarial networks | Long short-term memory

IJAIN (International Journal of Advances in Intelligent Informatics) , 2023

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SLOAN: Social Learning Optimization Analysis of Networks

David J. Lemay, Tenzin Doleck, Christopher G. Brinton

Online discussion research has mainly been conducted using case methods. This article proposes a method for comparative analysis based on network metrics such as information entropy and global network efficiency as more holistic measures characterizing so... see more

The International Review of Research in Open and Distributed Learning , 2022

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Design and Build a Mobile Application ‘Malaya.Id’ as a Medium for Business Networks in the Development of Msme’s

Rayie Tariaranie Wiraguna,Andro Agil,Nur Anita Yunikawati

Business networks are the most important thing in an effort to increase and expand market share and can help manage businesses to be more efficient. In expanding business networks, information technology plays an important role, especially in the use of w... see more

Mobile Applications | Business Networks | MSME Development

International Journal of Multicultural and Multireligious Understanding , 2022

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Online social network user performance prediction by graph neural networks

(1) Fail Gafarov (Kazan Federal University, Russian Federation) (2) Andrey Berdnikov (Kazan Federal University, Russian Federation) (3) Pavel Ustin (Kazan Federal University, Russian Federation)

Online social networks provide rich information that characterizes the user’s personality, his interests, hobbies, and reflects his current state. Users of social networks publish photos, posts, videos, audio, etc. every day. Online social networks (OSN) ... see more

Online social network | graph neural networks | professional performance | graph convolutional neural networks | social graph

International Journal of Advances in Intelligent Informatics , 2022

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Online social network user performance prediction by graph neural networks

(1) Fail Gafarov (Kazan Federal University, Russian Federation) (2) Andrey Berdnikov (Kazan Federal University, Russian Federation) (3) Pavel Ustin (Kazan Federal University, Russian Federation)

Online social network | graph neural networks | professional performance | graph convolutional neural networks | social graph

IJAIN (International Journal of Advances in Intelligent Informatics) , 2022

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