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Predicting Stock Market Movements Using Long Short-Term Memory (LSTM) 4

Predicting Stock Market Movements Using Long Short-Term Memo...

引用

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

作者： Fauzan, Achmad Susananggreainy, Maria Nathaniel, Nicholas 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 Jakarta11480 Indonesia

ISBN: (纸本)9798350318432

This paper explores using artificial intelligence (AI) to predict stock market movements and build optimal portfolios. The research methodology involves using LSTM networks to predict stock performance. The study aims to combine AI with human expertise to develop an intelligent trading system. The findings emphasize the importance of selecting appropriate AI approaches for accurate predictions and optimal portfolio management. The results of this study state that with LSTM, we can predict stock prices that are very close to their real prices. The average LSTM method in predicting stock prices is about 97.2938%. Average error obtained when using LSTM was 2.3223%. © 2023 IEEE.

关键词： Long short-term memory

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Performance Analysis on Web Development programming Language (Javascript, Golang, PHP)

Performance Analysis on Web Development Programming Language...

引用

2023 International Conference on Information Technology and Computing, ICITCOM 2023

作者： Nabiil, Arkaan Makmur, Bintang Hermawan Wijaya, Reynard Wiratama Santoso Gunawan, Alexander Agung 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)9798350359633

This paper aims to use an experimental approach to determine the best performing and most stable web programming languages for building a website. Through a comprehensive comparison of different languages such as Golang, JavaScript, and PHP, our research aims to provide valuable insights for developers when it comes to choosing the right web programming language for their next web development project. The objective is to identify the web programming language that offers the best performance and stability in terms of key metrics such as CPU utilization, response time, and scalability. Additionally, the study will also consider the unique set of advantages and disadvantages of each language, to provide a comprehensive assessment of their suitability for different web development projects. Ultimately, the goal of this research is to make it easier for developers to choose the best web programming language for their needs, and to ensure that the resulting website is fast, stable, and easy to maintain. Based on the research and comparison of different languages, it is found that Golang is the best choice for web development projects as it offers the best performance and stability in terms of key metrics such as CPU utilization, response time, and scalability. Additionally, Golang also has a unique set of advantages that make it suitable for different web development projects. © 2023 IEEE.

关键词： Websites

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Development of Sundanese Stemmer Based on Morphophonemics 10

Development of Sundanese Stemmer Based on Morphophonemics

引用

10th International Conference on ICT for Smart Society, ICISS 2023

作者： Maesya, Aries Arifin, Yulyani Zahra, Amalia Budiharto, Widodo BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Computer Science Binus Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339543

The Stemming Process is used to get the base word by removing the word affixes. The purpose of this study is to improve the algorithm in previous research by incorporating the Stemming Process into a morphophonemic approach for language processing based on rules (Rule Based) which is named AM Sundanese Stemmer (AMS). The AM Sundanese stemmer algorithm will utilize morpheme information to perform stemming on Sundanese words and analyze the phonemes in a word to identify the morphemes therein contained. The experimental process was carried out with 11,885 existing data and a sample of 546 words were taken to be stemmed. The test was carried out by comparing the algorithms of Nazief and Adriani, UG 18 and AMS. The test results showed that the AMS Algorithm was better than the Nazief Andriani Algorithm and the UG18 Algorithm with a high F-1 score of 87.52% and the comparison of the execution time of the AMS Stemmer Algorithm was 0.041403 seconds faster than the Nazief Andriani and UG 18 Algorithms. © 2023 IEEE.

关键词： Rule Based Stemming Sundanese Stemmer

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Improving Universal Rendering Performance on NuxtJS-based Web Application 11

Improving Universal Rendering Performance on NuxtJS-based We...

引用

11th International Conference on Cyber and IT Service Management, CITSM 2023

作者： Angkasa, Harta Farell, Darren Wijaya, Erik Hendrawan Putra Achmad, Said Fitrianah, Devi Bina Nusantara University School of Computer Science Cyber Security Program Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350305968

Universal rendering is a way to render a website by combining server and client-side rendering. Universal rendering promises to boost the performance and SEO score of the website. However, it can be computationally exhausting for the server. This prompts researchers to address this problem in multiple different environments. Two parameters that could be used to measure the aforementioned metrics are Time to First Byte (Or Latency) and Time to Interactive. This paper addressed the aforementioned problem of universal rendering in a NuxtJS-based web application. JMeter and Lighthouse was used to test each proposed solution's performance and SEO score. Initially, there are three proposed solutions: lazy loading, SSR caching, and asset compression. This research proves that the aforementioned solutions effectively improve universal rendering performance in NuxtJS version 3.0.0. Each method has its pros and cons. For example, lazy loading and SSR caching are effective for improving the latency score, while asset compression is effective for enhancing the TTI score. © 2023 IEEE.

关键词： Websites

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Random Forest Based QSAR Model Analysis for Predicting Drug Effectiveness Against Mycobacterium Tuberculosis Bacteria 11

Random Forest Based QSAR Model Analysis for Predicting Drug ...

引用

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

作者： Ekosputri, Alicia Josephine Ardianti, Amanda Anggreainy, Maria Susan Artanto, Brychan Fitriawati, Nora Valentina, Fanny Angelia Santoso, Vincent Kartamulya School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11530 Indonesia Bina Nusantara University Binus Online Learning Information Systems Department Jakarta11530 Indonesia

ISBN: (纸本)9798350389654

This research focuses on the use of machine learning methods, especially Random Forest, in designing tuberculosis drugs more effectively and efficiently. The research process begins with the creation of a QSAR (Quantitative Structure-Activity Relationship) model using a dataset from ChEMBL that includes compounds with activity against Mycobacterium tuberculosis. This model aims to predict the pIC50 value, which is an indicator of a compound's biological activity as a tuberculosis drug. The results of the Random Forest model showed high accuracy, which is 92%. This accuracy indicates that the model has a good ability in predicting the effectiveness of compounds against Mycobacterium tuberculosis. With this result, the developed model can be used as an auxiliary tool in the discovery of tuberculosis drugs and can be further developed to increase the effectiveness in drug research. © 2024 IEEE.

关键词： Prediction models

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AI Chatbot Technology to Predict Disease: A Systematic Literature Review 4

AI Chatbot Technology to Predict Disease: A Systematic Liter...

引用

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

作者： Velasco, Vincent Dedy Setiawan, Kevin Robert Sanjaya, Renaldo Susan Anggreainy, Maria 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

Artificial Intelligence (AI) and chatbot technology have emerged as promising solutions to improve healthcare services. AI chatbots can mimic human-like interactions and assist with tasks such as triaging patients and providing medical advice. This review focuses on the use of AI chatbots in predicting diseases, aiming to explore their effectiveness and potential for early intervention and treatment. The purpose of this systematic literature review is to analyze studies related to AI chatbot technology in disease prediction. A systematic literature review was conducted, analyzing a total of 24 selected journals based on predefined inclusion and exclusion criteria. The review protocol involved examining studies published from various years, with a particular emphasis on articles from 2020. The findings indicate that AI chatbots have the potential to play a significant role in predicting diseases and assisting healthcare professionals in making informed decisions. AI chatbot technology shows tremendous potential in disease prediction. By utilizing machine learning algorithms and techniques, chatbots can enhance the accuracy and quickness of disease diagnosis. Continued research and development efforts are necessary to refine AI chatbots' capabilities and revolutionize healthcare delivery for improved patient outcomes and disease management. © 2023 IEEE.

关键词： Diagnosis

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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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Raising Cyber Security Awareness to Reduce Social Engineering Through Social Media in Indonesia 3

Raising Cyber Security Awareness to Reduce Social Engineerin...

引用

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

作者： Reuben, Nathanael Irawan, Rionel Jovann, Rainer Nathanael 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

In this day and age, there has been a surging increase in the use of social media such as Instagram, Facebook, Twitter, TikTok, etc. This kind of technology is useful to entertain and communicate in our daily life. But there is also a negative side to this technology, and one of them is social engineering. People will sometimes trick you into getting information that you shouldn't give to strangers, and sometimes people fall for this trick. This research aims to investigate the impact of social engineering infographics on the Indonesian populace's awareness of the issue. The t test reveals significant differences between the two survey groups that were informed beforehand about social engineering and those that were not. Infographics have a positive effect on individuals, making them more aware of social engineering cases. © 2023 IEEE.

关键词： Cybersecurity

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A Survey Study of Social Media User Awareness Towards Personal Identifiable Information's Data Security in Indonesian Millennial Generation 3

A Survey Study of Social Media User Awareness Towards Person...

引用

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

作者： Christie, Gabriel Alexander Ivan Trevan, Javier 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

Online Social Network is a network communication platform where users have profiles that can be uniquely identified by the content sent. This content can be produced, consumed, and interacted with by other users. To connect with other users on social media, users must register by providing Personally Identifiable Information (PII) to social media platforms. PII is specific information that can identify or track individuals directly. This specific information may include your name, address, social security number, or other identifying code numbers such as telephone numbers, email addresses, and others. Personal identifiable information leakage is a problem in data security. Basically, every individual does not want their personal data to be known by anyone. Utilizing a sample size of 50 respondents, this study aims to ascertain the percentage of individuals who are aware of PII security on social media. This research will use quantitative methods by distributing questionnaires. The questionnaire in this study uses a social media attribute design. The results of the survey indicate that many respondents are unaware of the security of their data and have a limited understanding of how their personal data is managed by technology companies, particularly the 80% of non-IT respondents. © 2023 IEEE.

关键词： Social networking (online)

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Authorship Attribution in Bahasa Indonesia Using Twitter Dataset on Political Topic 4

Authorship Attribution in Bahasa Indonesia Using Twitter Dat...

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

作者： Muliono, Yohan Gaol, Ford Lumban Chowanda, Andry Budiharto, Widodo Bina Nusantara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350318432

Fake news so called made-up news intended to cause misinformation is identified as Hoax. In Indonesia, hoaxes could not be ignored, fairly low literacy rate is the cause of hoaxes could spread quickly in Indonesia, to make it even worse, there are so many people would believe in hoaxes without any intention to make sure of the integrity of the news. even the media in Indonesia are competing with one another to provide content with provocative names in the hopes of increasing their rating and reaching as many people as possible. In the course of this research, a method for identifying authors on the basis of their writings will be developed to reduce the spread of hoaxes and encourage people to re-evaluate their decision to create harmful content and hoax news in the future. In this investigation, a transformer-based methodology focusing on IndoBERTbase, IndoBERTbase-uncased, and IndoBERTtweet will be employed in conjunction with the self-collected Indonesian tweet data that will be crawled from Indonesian Social Actor Focused on politicians in Twitter and will be combined with another topic in the future study. This research has shown a promising 98,93% in Training Accuracy using IndoBERTtweet. © 2023 IEEE.

关键词： Curricula

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