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Detection Traffic Congestion Based on Twitter data using Machine Learning

Procedia computer science 2019年 157卷 118-124页

作者： Muhammad Taufiq Zulfikar Suharjito Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Binus Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Twitter is one of the social media with text and image information that can be used as a source of information to detect traffic congestion in real-time. This study developed a system to detect traffic congestion in Indonesia, especially DKI Jakarta. The system displays the direction of the street according to the name of the street being passed and from each of the names of the streets, resulting in a tweet from the classification. The proposed method uses the Support Vector Machine (SVM) classification with the sigmoid kernel. This study shows that the SVM classification with the sigmoid kernel (libSVM) has an accuracy rate of 96.24% and that was increased by 2.68% when compared to SVM dot (mySVM). Based on the evaluation result of the proposed system compare to google maps application on detecting traffic congestion, the system could find a similar condition as many as 17 times from 25 of testing.

关键词： Traffic Congestion Text Classification Support Vector Machine

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A Cybersecurity Framework for Home Energy Management Systems using Artificial Intelligence 32

A Cybersecurity Framework for Home Energy Management Systems...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Gunasekara, Lakshitha Moraliyage, Harsha Silva, Daswin De Mills, Nishan Alahakoon, Damminda Jennings, Andrew Manic, Milos La Trobe University Centre for Data Analytics and Cognition Melbourne Australia Virginia Commonwealth University Department of Computer Science Richmond United States

ISBN: (纸本)9798350399714

Home Energy Management Systems (HEMS) have become a pivotal component of the smart grid infrastructure as they facilitate energy exchange and trading. With the increasing use of micropower renewables generation from wind and solar within residential houses and buildings, HEMS now plays a critical role in not just managing energy usage but assisting the smart grid with schedule optimisation. However, HEMS are typically installed with limited security measures, which makes them vulnerable to cyber-attacks. A coordinated attack on multiple HEMS has the potential to compromise the entire power grid. In this article, we aim to address this gap by proposing a robust security framework for HEMS. The framework centralises security in the design of HEMS and leverages Artificial Intelligence for the security requirements. The proposed framework consists of five layers with built-in security measures that use AI to mitigate cyber threats. This is a key contribution that has been neglected in related work in optimizing HEMS operations. © 2023 IEEE.

关键词： Smart power grids

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Text-based Depression Detection on Social Media Posts: A Systematic Literature Review

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Procedia computer science 2021年 179卷 582-589页

作者： David William Derwin Suhartono Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

Due to the huge increase of awareness of mental health well-being, the detection of mental illness itself is starting to become a huge concern. Many psychiatrists found difficulties in identifying the existence of mental illness in a patient because of the complicated nature of each mental disorder, thus making it hard to give the appropriate treatment to the patient before it’s too late. However, due to the integration of social media into people’s daily life, this create an environment that may provide additional information regarding the mental disorder a patient bear. This study has been undertaken as a Systematic Literature Review (SLR), which is defined as a process of identifying, assessing, and interpreting the available resources to provide answers for a set of research questions. Analysis is made to answer questions regarding text-based mental illness detection based on the social media activity of people with mental disorders, and reveals that it indeed is possible to do early detection of depression on social due to the existence of a particular characteristics in the way these subjects use their social media. This SLR found that from the small amount of research using text-based approach, most studies use deep learning models such as RNN on the early detection of depression cases due to the limitation of data availability. However, this study will look to find method that may prove to be more effective.

关键词： Linguistic analysis Natural language processing Depression detection Social media

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Optimum Nutrition Intake from Daily Dietary Recommendation for Indonesian Children using Binary Particle Swarm Optimization Algorithm

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Procedia computer science 2019年 157卷 16-24页

作者： Fanny Lili Ayu Wulandhari Sani Muhamad Isa Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Binus Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Optimum nutrition intake in daily dietary habit has a significant role for children growth. Nevertheless, the mistakenness in the fulfillment of nutrition still concerned. It happens because an individual does not have much knowledge about the energy content of food and food combination to meet the nutrition requirement. The objectives of this research are to facilitate an individual to obtain the optimum nutrition intake from their daily dietary habit. This paper proposes a Binary Particle Swarm Optimization (BPSO) algorithm to find the optimum combination of food portion and food option for an individual daily dietary habit. The food data is obtained from ’Tabel Komposisi Pangan Indonesia ’ book which contains more than 1600 kind of Indonesian food. The results show that BPSO provides an optimum nutrition intake accuracy of 99.14%. Moreover, the nutritionist is already validated that this experiment is succeed in recommending a variation of daily dietary habit that meet an optimum nutrition intake for an individual. Based on this result it can be conducted that BPSO can provide the better accuracy of optimum nutrition intake than Genetic Algorithm (GA), while GA can only provide an optimum nutrition intake accuracy of 97.87%.

关键词： Optimum nutrition Energy requirement Energy intake Dietary habit recommendation Binary Particle Swarm Optimization

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Injections Attacks Efficient and Secure Techniques Based on Bidirectional Long Short Time Memory Model

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computers, Materials & Continua 2023年第9期76卷 3605-3622页

作者： Abdulgbar A.R.Farea Gehad Abdullah Amran Ebraheem Farea Amerah Alabrah Ahmed A.Abdulraheem Muhammad Mursil Mohammed A.A.Al-qaness School of Big Data&Software Engineering Chongqing UniversityChongqing401331China Department of Management Science Engineering Dalian University of TechnologyDalian116024China Software College Northeastern UniversityShenyang110169China Department of Information Systems College of Computer and Information ScienceKing Saud UniversityRiyadh11543Saudi Arabia Department of Management Science and Engineering South China University of TechnologyGuangzhou510641China Department of Computer Engineering and Mathematics University of Rovira i VirgiliTarragonaSpain College of Physics and Electronic Information Engineering Zhejiang Normal UniversityJinhua321004China

E-commerce,online ticketing,online banking,and other web-based applications that handle sensitive data,such as passwords,payment information,and financial information,are widely *** web developers may have varying levels of understanding when it comes to securing an online *** Query language SQL injection and cross-site scripting are the two vulnerabilities defined by the OpenWeb Application Security Project(OWASP)for its 2017 Top Ten List Cross Site Scripting(XSS).An attacker can exploit these two flaws and launch malicious web-based actions as a result of these *** published articles focused on these attacks’binary *** article described a novel deep-learning approach for detecting SQL injection and XSS *** datasets for SQL injection and XSS payloads are combined into a single *** dataset is labeledmanually into three labels,each representing a kind of *** work implements some pre-processing algorithms,including Porter stemming,one-hot encoding,and the word-embedding method to convert a word’s text into a *** model used bidirectional long short-term memory(BiLSTM)to extract features automatically,train,and test the payload *** payloads were classified into three types by BiLSTM:XSS,SQL injection attacks,and *** outcomes demonstrated excellent performance in classifying payloads into XSS attacks,injection attacks,and non-malicious ***’s high performance was demonstrated by its accuracy of 99.26%.

关键词： Web security SQL injection XSS deep learning RNN LSTM BiLSTM

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A Comparison of Prediction Methods for Credit Default on Peer to Peer Lending using Machine Learning

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Procedia computer science 2019年 157卷 38-45页

作者： Netty Setiawan Suharjito Diana Computer Science Department Binus Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Social lending or peer to peer lending (p2p lending) has emerged as a viable digital platform where lenders and borrowers can do business without the involvement of financial institutions. P2p lending has gained significant momentum recently, with some platform has reached billion-dollar loan circulation. However, p2p lending platforms are not free from any form of risks. A higher return on investment for investor comes with a risk of the loan and interest not being repaid. For this purpose, this research proposes a tree-based classification method for predicting whether a loan will go bad or default before the loan is approved. The high dimensionality of the dataset needs to be processed and chosen carefully. This paper proposes a Binary PSO with SVM to perform feature selection for the dataset and Extremely Randomized Tree (ERT) and Random Forest (RF) as the classifiers. In this research, BPSOSVM-ERT and BPSOSVM-RF are compared with several performance metrics. The experimental results show BPSOSVM can produce subset of features without decreasing the performance from the original features and ERT can outperform RF in several performance metrics.

关键词： P2P lending Random forest Extremely randomized tree PSO BPSO

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The Social Media Implications on the Sales of Business Products 3

The Social Media Implications on the Sales of Business Produ...

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3rd International Conference on Smart data Intelligence, ICSMDI 2023

作者： Jacia, Elvina Dyan, Gabriel Ifan, Amelia Gaol, Ford Lumban Matsuo, Tokuro Bina Nusantara University Alam Sutera Department of Information System Indonesia Binus Graduate Program-Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9781665464871

The use of technology nowadays does not feel strange. Everyday people who use technology for their daily needs, starting with each other, seeking knowledge, can even earn income by doing business using technology. Social media is a tool that can be used by people to become with each other by creating, sharing, and exchanging information virtually through a network. However, in the current era, the notion of social media is not only about exchanging information, but also to support business products. The problem is how to compete tightly in this modern era in increasing the selling value of business products. The positive impact of social media for sales in business products are huge such as, increase sales, increase product promotion, greater market distribution. On the other side, the negative impact also takes part such as, the more competitors, the products compete fiercely in the market. This research aims to identify more the impact of social media on sales of business products that focused on business, benefit, and factor. The research method that we used is quantitative which focuses on the number of samples of respondents to support the research results and the results are in the form of a graphic that shows the answers of the respondents to the questionnaire. © 2023 IEEE.

关键词： Sales

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Style Transfer of Musical Performance Expression Using Note Classification Based on the Implication-Realization Model 23

Style Transfer of Musical Performance Expression Using Note ...

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7th International Conference on computer science and Application Engineering, CSAE 2023

作者： Mizutani, Tetsuya Sasaki, Shigefumi Department of Information Engineering University of Tsukuba Tsukuba Japan Master's Program in Computer Science University of Tsukuba Tsukuba Japan

ISBN: (纸本)9798400700590

In recent years, the style transfer is being studied in the field of AI. It extracts a style from one data set and applies to another data set. This technique is actively studied mainly in computer vision. It is also being studied in music and speech processing with many deep learning methods. However, no research focused on changes in performance expression of music. Performance expression of music refers to the player's artistic interpretation of a piece of music, the changes in performance, and the techniques used to achieve these changes. Changes in performance are represented by slow and fast beats, changes in strength and weakness. In this study, as a part of the study of analysis and creation of performance expression models of music, the image style transfer method is applied to musical expression. In addition, in order to analyze the relationship between musical structure and musical expression, the implication-realization model of music theory is used to extract the structure of music to improve the performance of style transfer. The analysis result shows that the I-R model captures the feature of musical expression well, and moreover, the style transfer method is shown to be useful for analyzing performance expression of music. It will lead to the study of music performance expression style extraction and will contribute to the analysis and creation of performance expression models of music. © 2023 ACM.

关键词： Music

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Sentiment Analysis of the Indonesian Police Mobile Brigade Corps Based on Twitter Posts Using the SVM and NB Methods

Sentiment Analysis of the Indonesian Police Mobile Brigade C...

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International Conference on Electronics Representation and Algorithm 2019, ICERA 2019

作者： Pratama, Bryan Saputra, Dedi Dwi Novianti, Deny Purnamasari, Endah Putri Kuntoro, Antonius Yadi Hermanto Gata, Windu Wardhani, Nia K Sfenrianto, Sfenrianto Budilaksono, Sularso Master of Computer Science-Postgraduate Program STMIK Nusa Mandiri Jakarta Indonesia Graduate School Master's Degree Computer Science STMIK Nusa Mandiri Jakarta Indonesia Master Faculty of Computer Science-Postgraduate Program Universitas Mercubuana Jakarta Indonesia Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Graduate School Master's Degree Computer Science Universitas Persada Indonesia YAI. Jakarta Indonesia

The Brimob Corps is a special police force, just like the special military detachments held by the TNI such as Paskhas and so on. At present brigade corps police national is busy being discussed in the real world and cyberspace, especially on social media twitter. Many opinions about the brigade corps police national so there are positive and negative opinions. Social media twitter is now one places to spread information about brigade corps police national. This study cases uses text mining techniques with support vector machine (SVM) method which aims to classify public sentiments towards brigade corps police national on twitter. The dataset used is tweet in Indonesian with keyword "Brimob" with a total dataset of 1000 tweets. Text mining, transform, tokenize, stemming, and classification, etc. techniques are useful for building classification and analysis of sentiment. RapidMiner and Gataframework are also used to help create sentiment analysis to measure classification values. Accuracy values obtained with support vector machine (SVM) approach 86,96%, with precision values of 86,96%, and recall values of 86,96%. © Published under licence by IOP Publishing Ltd.

关键词： Law enforcement

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Braess paradox in dynamic routing for the cohen-kelly network

Braess paradox in dynamic routing for the cohen-kelly networ...

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Fourth IASTED International Conference on Communications, Internet, and Information Technology, CIIT 2005

作者： Inoie, Atsushi Kameda, Hisao Touati, Corinne E. Doctoral Program in Computer Science University of Tsukuba Tsukuba Sci. City Ibaraki305-8573 Japan Department of Computer Science University of Tsukuba Tsukuba Sci. City lbaraki305-8573 Japan

ISBN: (纸本)0889865159

A paradox of dynamic routing in the Cohen-Kelly network is studied. Intuitively, we expect that adding capacity to a network improves the performance of the users. Braess showed an example wherein the opposite occurs. We refer to such a situation as a paradox. In this paper, we deal with a class of queueing networks in which Cohen and Kelly discovered a paradox in static routing. We consider the dynamic routing problems in the above mentioned class of networks, and show the existence of a paradox in dynamic routing of the above mentioned class of networks through simulation experiments analogous to what Cohen and Kelly showed.

关键词： Routers

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