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检索条件"机构=Program Computer Science"

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U-Net Based Vegetation Segmentation for Urban Green Space (UGS) Regulation in Yogyakarta City 8

U-Net Based Vegetation Segmentation for Urban Green Space (U...

引用

8th International Conference on Informatics and Computing, ICIC 2023

作者： Putri, Delfia Nur Anrianti Wijaya, Raden Bagus Muhammad AdryanPutra Adhy Nailfaaz Wahyono Computer Science Undergraduate Program Faculty of Mathematics and Natural Science Sleman Indonesia Faculty of Mathematics and Natural Science Department of Computer Science and Electronics Sleman Indonesia

ISBN: (纸本)9798350342604

Urban Green Space (UGS) plays a vital role in maintaining the balance of urban ecosystems. In Yogyakarta City, urban development and an increase in population accompanied by a decrease and insufficiency in the proportion of UGS correlate with rising urban temperatures. Monitoring the availability of UGS can serve as a foundation for decision-making in managing the city's UGS. With advancements in technology and computing in the field of computer Vision (CV), it's possible to recognize UGS from the geometric patterns of satellite images. This study proposes a vegetation segmentation method using satellite images and a Deep Learning (DL) method with the U-Net architecture to estimate the availability of UGS. Evaluation results show that the image dataset without preprocessing with the Red Green Blue (RGB) color channel gives an average Intersection over Union (IoU) of 80.74%. These results are better than data that underwent grayscaling and contrast stretching preprocessing. Based on a case study conducted in three sub-districts in the Yogyakarta region, the constructed U-Net model gave an average IoU evaluation of 60.88%. These results demonstrate the model's capability to provide a reference in calculating the UGS area at the sub-district level, which can then be utilized by the Yogyakarta City government to analyze the availability of UGS more efficiently. With this analysis, the government can make strategic decisions to manage UGS and create a sustainable urban environment. © 2023 IEEE.

关键词： Remote sensing

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Air Pollution Level Prediction in Jakarta Using Artificial Neural Network 4

Air Pollution Level Prediction in Jakarta Using Artificial N...

引用

4th International Conference on Artificial Intelligence and Data sciences, AiDAS 2023

作者： Ferdinan, Roger Margareta, Krestella Christyan, Stevan Anggreainy, Maria Susan Kurniawan, Afdhal School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta11530 Indonesia

ISBN: (纸本)9798350318432

Air pollution has emerged as a critical issue in several major urban areas, including Jakarta. To address this problem, the study explores the utilization of the Artificial Neural Network (ANN) method. Three distinct approaches are investigated in this research: the Support Vector Classifier (SVC), Deep Artificial Neural Network (Deep ANN), and Long Short-Term Memory (LSTM). The available Air Quality data were utilized to train and assess the performance of the proposed ANN models. The research findings reveal that the Deep ANN model surpasses the other methods, achieving an impressive accuracy of approximately 96.57% and a cross-entropy value of 0.1103. In predicting air quality in Jakarta, Deep ANN has demonstrated superior performance when compared to SVC and LSTM. These results highlight the significant potential of deploying Deep Artificial Neural Network (ANN) methodologies for air quality prediction. Such an approach could play a pivotal role in the development of monitoring and early warning systems aimed at effectively addressing air quality issues in the Jakarta region. © 2023 IEEE.

关键词： Long short-term memory

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Systematic Literature Review on IT Strategic Workspaces: Approach to Develop an Ideal Environment 9

Systematic Literature Review on IT Strategic Workspaces: App...

引用

9th IEEE International Conference on Computing, Engineering and Design, ICCED 2023

作者： Putra, Alden Ardiwinata Fusanto, Princessa Fortunata Valonika, Nebrisca Anggreainy, Maria Susan Kurniawan, Afdhal Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia BINUS Graduate Program Doctor of Computer Science Computer Science Department Bina Nusantara University Jakarta11530 Indonesia

ISBN: (纸本)9798350370126

Technology and information will always develop dynamically;this statement demands programmers to always be creative and keep up with the times. Despite this, their work ethic is always the same and tends to stagnate. programmers' perspectives on their workplace: this perspective is rarely seen as important and the opportunity for a comprehensive study is still widely open. This study aims to conduct a systematic literacy study to ascertain that the workplace has a crucial relationship with a programmer's performance. The focus of the study includes a discussion of how programmers relate to their workplace in a tech company, benchmarking between various office layouts, and criteria that can be derived from the literature review regarding a degree of whether such a workplace is good or bad. The proper base facts are obtained. Nevertheless, the two entities are proven to be interrelated to each other. Such correlations are derived into tangible metrics and parameters (e.g., human cognitive, cultural, physical, behavioral, etc.). Relating issues regarding these topics are also presented. © 2023 IEEE.

关键词： Software engineering

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An Analysis of Hate Speech Detection Techniques 4

An Analysis of Hate Speech Detection Techniques

引用

4th International Conference on Artificial Intelligence and Data sciences, AiDAS 2023

作者： Krisdianto, Ricky Apriani, Ivana Halim, Peter Miracle Anggreainy, Maria Susan Kurniawan, Afdhal School of Computer Science Bina Nusantara University Computer Science Departement Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Departement Jakarta11480 Indonesia

ISBN: (纸本)9798350318432

Hate speech is any act of provoking or insulting another person or group based on their ethnicity, religion, race, gender, sexual orientation, physical ability, or other characteristics. This can be done in a variety of ways. Because of this, a study was conducted that focused on ascertaining the most effective technique for identifying hate speech. It was discovered that LSTM, a form of recurrent neural network (RNN) that is particularly good at modeling sequential data, is the most successful technique to apply. Many natural language processing (NLP) activities may be performed with it, including hate speech detection, which makes LSTM have advantages over other techniques, both in terms of long-term memory mechanisms. LSTM, also able to handle long and complex text sequences, capable of recognizing more complex patterns, able to understand and consider the context in the text, to recognize the meaning of a word or phrase in a broader context. Then, based on the dataset obtained from the Kaggle website with a total of 24783 data, then the dataset is divided into training data and validation data, with a ratio of training data to validation data. of 80%: 20%. Then, the testing step results in an accuracy value of 87.10%. © 2023 IEEE.

关键词： Speech recognition

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Computational Analysis of Jazz Music: Estimating Tonality through Chord Progression Distances 23

Computational Analysis of Jazz Music: Estimating Tonality th...

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

作者： Yamamoto, Yuta Mizutani, Tetsuya Master's Program in Computer Science University of Tsukuba Tsukuba Japan Department of Computer Science University of Tsukuba Tsukuba Japan

ISBN: (纸本)9798400700590

Currently, research in music informatics focuses extensively on music theory, particularly on the theoretical systems of Western classical music dating back to the 19th century. However, contemporary popular music genres such as pop, rock, and jazz often rely on jazz music theory, which is an evolution from classical music theory. To make music informatics research more practical and relevant to modern music composition, it is essential to explore music analysis based on jazz music theory using computational methods. In this study, we attempt to perform jazz music analysis computationally. Jazz music theory primarily centers around chord progressions. Therefore, Tonal Pitch Space (TPS) and its extension to jazz music theory, TPS-ExJ, are valuable tools for our investigation. We implement and modify these computational music theories to calculate the "chord distance,"a metric indicating the naturalness of chord progressions. This allows us to estimate the "key"of a piece of music, a concept determined by human sensibility, using computational techniques. Although the experimental results for key estimation are not particularly high, we believe that the theoretical framework proposed in this study forms a solid foundation for complex chord progressions' key estimation in jazz music. © 2023 ACM.

关键词： Music

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Phishing Attack Awareness Among College Students 3

Phishing Attack Awareness Among College Students

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3rd International Conference on Electronic and Electrical Engineering and Intelligent System, ICE3IS 2023

作者： Kenneth, Alvin Hayashi, Bernard Bryan Lionardi, Jason Richie, Stevanus Achmad, Said Junior, Franz Adeta Nadia School of Computer Science Bina Nusantara University Cyber Security Program Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350327762

Phishing is a form of cyber-attack that uses social engineering techniques to trick individuals into providing sensitive information or clicking on malicious links, often through email or text messages. Social engineering is the psychological manipulation of people into performing actions or disclosing sensitive information. In phishing, attackers use social engineering tactics such as creating a sense of urgency, posing as a trustworthy entity, and creating a sense of familiarity to manipulate the victim into taking the desired action. These attacks can have serious consequences, including financial loss and identity theft. In this research, we used an email phishing technique that asked respondents to change their password on an email account to find out awareness of phishing attacks on college students. The research results show that a small percentage of a certain amount of people are still unaware of phishing attacks and fell into the attacker's trap. Several respondents who are still deceived by social engineering using phishing emails indicate that it is necessary to conduct indoctrination and campaigns to raise the awareness of each student. © 2023 IEEE.

关键词： Electronic mail

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Development of Smart Lights to Reduce Electricity Usage by Using Fuzzy Logic 1

Development of Smart Lights to Reduce Electricity Usage by U...

引用

1st IEEE International Conference on Smart Technology, ICE-SMARTec 2023

作者： Djayapranata, Daniel Thetrasakti, Renaldy Arnaldo Theodora, Regina Gunawan, Alexander Agung Santoso Edbert, Ivan Sebastian School of Computer Science Bina Nusantara University Cyber Security Program Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350306156

In wealthy nations, the demand for electrical energy is steadily increasing, despite the scarcity of available resources. Considering that individuals spend approximately 80% of their lives indoors, it is imperative to implement energy-efficient lighting solutions to reduce electricity consumption. In this research, we have developed a prototype of an intelligent lamp that employs LUX sensors and fuzzy logic to automatically adjust power usage based on ambient light levels. The primary objective of this study is to minimize energy wastage through experimentation with the prototype's performance. Our findings indicate that, depending on the room's lighting conditions, this innovative smart lamp can achieve an average energy savings of 45.46%. © 2023 IEEE.

关键词： Fuzzy logic

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The Usage of Machine Learning on Penetration Testing Automation 3

The Usage of Machine Learning on Penetration Testing Automat...

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3rd International Conference on Electronic and Electrical Engineering and Intelligent System, ICE3IS 2023

作者： Clintswood Lie, Delbert Giovanni Kuswandana, Lexiandy Nadia Achmad, Said Suhartono, Derwin School of Computer Science Bina Nusantara University Cyber Security Program Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350327762

Penetration testing is a method to assess the security within a network by performing or simulating a real-world cyber-attack on the network. It has been one of the best ways preferred by organizations to strengthen their network defenses against cyber threats. However, penetration testing proves that it has several drawbacks such as requiring a significant number of skills and time to perform. A survey made by The International Information System Security Certification Consortium also shows that the world is lacking cybersecurity workforces. To address this problem, this paper conducts research regarding the usage of machine learning to automate penetration testing activity. To start off, automated penetration testing tools will be created using machine learning algorithms, specifically reinforcement learning and deep reinforcement learning algorithms. The second step is to put the tools in a learning stage where it will be provided with the MITRE ATT&CK Framework. This framework will be the base for the attacks and exploitations used within the tools. The third step is to conduct a series of automated penetration testing over different target networks. The result will be then compared and analyzed with a manual penetration testing report to see how efficient and better it is compared to a manual penetration test. Lastly, the final data will then be collected for future developments and recommendations. © 2023 IEEE.

关键词： Cybersecurity

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Sentiment Analysis for TikTok Review Using VADER Sentiment and SVM Model 8

Sentiment Analysis for TikTok Review Using VADER Sentiment a...

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8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Isnan, Mahmud Elwirehardja, Gregorius Natanael Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

TikTok, a social networking site for uploading short videos, has become one of the most popular. Despite this, not all users are happy with the app;there are criticisms and suggestions, one of which is reviewed via the TikTok app on the Google Play Store. The reviews were extracted and then used for training a sentiment analysis model. The VADER sentiment method was utilized to offer the review's initial labeling (positive, neutral, and negative). The result revealed that most reviews were classified as positive, meaning that the data were imbalanced and challenging to handle in further analysis. Therefore, Random Under-sampling (RUS) and Random Over-sampling (ROS) methods were deployed to deal with that condition. The labeled reviews were subsequently pre-processed using tools such as case folding, noise removal, normalization, and stopwords before being used for training a Support Vector Machine (SVM) model for sentiment classification. The SVM trained without resampling produced the most favorable results, with an F1-score of 0.80. © 2023 The Authors. Published by Elsevier B.V.

关键词： Google Play Store Sentiment Analysis SVM TikTok VADER Sentiment

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Analysis of the Utilization of Human Motion Tracking in the Security Sector: Examining the Accuracy Level and Key Factors in Operation 6

Analysis of the Utilization of Human Motion Tracking in the ...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Indradjaja, Nicholas Chen, Michael Masada, Hossey Anggreainy, Maria Susan Kurniawan, Afdhal School of Computer Science Computer Science Department Bina Nusantara University Jakarta11480 Indonesia BINUS Graduiate Program Doctor of Computer Science Computer Science Department Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798350358346

The use of surveillance cameras (CCTV) is very limited and has many weaknesses. Surveillance cameras can only record events that are happening without being detected, so supervisors still need protection. From these limitations, it is necessary to use Human Motion Tracking on surveillance cameras that can help detect objects caught on camera. This paper analyzes each Human Motion Tracking method in terms of the level of accuracy of the supporting or inhibiting factors, as well as the estimated costs required. This paper will compare each of the methods found to conclude that the Human Motion Tracking method has the highest detection accuracy, equipped with adequate key factors, and accompanied by a balanced cost. In conclusion, this study recommends the Kalman Filter method as the most optimal choice for human Motion Tracking on surveillance cameras, offering a balanced combination of accuracy and efficiency. The implementation of this method is expected to contribute significantly to enhancing security measures and creating a safer environment by effectively monitoring potential security issues. © 2023 IEEE.

关键词： Cameras

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