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

作者： Purwandari, Kartika Perdana, Reza Bayu Sigalingging, Join W.C. Rahutomo, Reza Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Database Center Division of BMKG Meteorological Climatological and Geophysical Agency Jakarta10720 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Although Twitter is a popular platform for social interaction analysis and text data mining, it faces challenges with geolocation automation. To address this problem, the researchers propose the utilization of a Support Vector Machine (SVM) model to develop an automated Twitter crawling system. The system aims to collect data related to weather in Indonesia by employing Twin, a Python-based Twitter scraping software. To overcome null geolocations, the study incorporates aliases created based on the common practice of Indonesian users mentioning the country's location in tweets. The results demonstrate that the SVM model, combined with automated smart crawling, achieves an 85% accuracy rate. © 2023 The Authors. Published by Elsevier B.V.

关键词： smart crawling Social media SVM Twitter weather

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Exploring the Relatedness of Educational Technology in Enhancing Study Performance 8

Exploring the Relatedness of Educational Technology in Enhan...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Othman, Norfaridatul Akmaliah Alamsyah, Doni Purnama Siswanto, Boby Morika, Doni Wijaya, Billiam Christofer Adinda, Putri Giyan Universiti Teknikal Malaysia Melaka Department of Management Technology Melaka76100 Malaysia Binus Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

The research design is to explore about support from perceived relatedness and students satisfied on the individual performance of online learning. The research spotlight on the behavior users regarding to e-learning, where the users is experienced student on e-learning. There were 663 users whose data was collected through online questionnaires. Data from users is processed using the Structural Equation Model with SmartPLS. The study results show that there is a relationship from perceived relatedness to increasing the satisfaction and performance of students learning. Student achievement is important because it can mediate and support study performance. Relatedness supports well the behavior of users related to adaptation to e-learning. Empathy, friendliness, affiliation and caring from students are considered in the evaluation of perceived relatedness. Studies on education technology reinforce the sustainable of academic performance through online learning concepts. © 2023 IEEE.

关键词： Students

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Performance Variations in Digital Talent: Gender-Based Insights from STEM and AI Education Backgrounds

Performance Variations in Digital Talent: Gender-Based Insig...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Erwin Halim Azani Cempaka Sari Irma Kartika Wairooy Muhamad Keenan Ario Said Achmad Devi Fitrianah Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

In the digital era, digital talent development has become increasingly vital for organizations and economies to thrive. While much focus has been placed on technical skills, this report emphasizes the often-overlooked role of soft skills in developing digital talent. Through an extensive literature review and data analysis, the study identifies that soft skills are crucial in enhancing digital talent performance. This research explores the factors that influence Digital Talent Performance in Indonesia, specifically comparing the performance levels of male and female digital talents. Data were collected from college students in the Jabodetabek area (cities surrounding Jakarta, Indonesia) using a purposive sampling method, with an online questionnaire distributed to 378 respondents. The study utilized Structural Equation Modeling (SEM) to analyze the collected data using SmartPLS 4.1. software. Key variables examined include Communication Skills, Teamwork, Emotional Intelligence, Academic Achievement, Problem-Solving, Digital Readiness, Digital Skills, Digital Technology, and Digital Talent Performance. Out of the nine hypotheses tested, one was not statistically significant. The results suggest that a combination of both technical and soft skills significantly affects digital talent performance, with important gender-based differences in performance levels emerging from the analysis. This research contributes to understanding Indonesia's complex dynamics of digital talent development.

关键词： Numerical analysis Education Urban areas Sampling methods Mathematical models Software Teamwork Problem-solving Artificial intelligence Systematic literature review

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Recurrent Neural Network-based Models as Bahasa Indonesia-Sundanese Language Neural Machine Translator

Recurrent Neural Network-based Models as Bahasa Indonesia-Su...

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computer science, Information Technology and Engineering (ICCoSITE), International Conference on

作者： Bambang Dwi Wijanarko Yaya Heryadi Dina Fitria Murad Cuk Tho Kiyota Hashimoto Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Prince of Songkla University Phuket Thailand

Sequential data are available in many domains including weather observation data, stock price, gene sequence, and many others. Sequential data processing is very instrumental as a solution to a variety of downstream tasks in Natural Language Processing such as language translation. Translating a language to another language has become instrumental when peoples interact with other people who speak a different language. However, language translation is not an easy computation task when there is a language-resource gap. This paper presents some empirical results from the exploration of the Recurrent Neural Network (RNN), the Gated Recurrent Unit (GRU), the Long Short-term Memory (LSTM), and the Bidirectional Long Short-term Memory (Bi-LSTM) models as machine translation models from Bahasa Indonesia to the Sundanese language. These empirical results show that the Bi-LSTM achieved the highest performance (0.95 average training accuracy and 0.92 average testings BLEU score) compared to the RNN (0.93 average training accuracy and 0.91 average testings BLEU score), the GRU (0.88 average training accuracy and 0.89 average testings BLEU score), and the LSTM (0.92 average training accuracy and 0.91 average testings BLEU score) models. These results validate some previously reported studies that claim the Bi-LSTM model potentially outperforms the other recurrent neural network-based models when it is used to process sequence datasets.

关键词： Training Recurrent neural networks Computational modeling Instruments Data processing Machine translation Task analysis

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Data mining for epidemiology: The correlation of typhoid fever occurrence and environmental factors 7

Data mining for epidemiology: The correlation of typhoid fev...

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7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Asadi, Faisal Trinugroho, Joko Pebrianto Hidayat, Alam Ahmad Rahutomo, Reza Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information System Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia

Typhoid fever is an endemic disease that burdens Indonesia and has a potentially fatal infection multisystem. Salmonella typhi bacterium is responsible for typhoid fever disease. Poor sanitation, crowding, and slums are the main factors of increasing typhoid fever incidences. Environmental factors directly connected to meteorological factors are the main factor in breeding the Salmonella typhi bacterium. This study aims to identify the correlation between meteorological parameters and typhoid fever disease occurrence. The study was carried out in Jakarta, Indonesia, and the Bureau of Meteorological, Climatology, and Geophysics (BMKG) provided the meteorological parameter data. In addition, the Jakarta health surveillance office provided information on typhoid fever hospitalizations from 2019 to 2021. Pearson's concept was utilized d to investigate the correlation between typhoid fever incidences and the meteorological parameters. Humidity, precipitation, and wind speed are the meteorological parameters that significantly affect in contribute to the occurrence of typhoid fever disease. These findings might be used as a reference for Indonesia's government in making public policy to prevent typhoid fever in Indonesia. © 2022 Elsevier B.V.. All rights reserved.

关键词： Data mining

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LLM2Vec Sentence Embeddings Analysis in Sentiment Classification

LLM2Vec Sentence Embeddings Analysis in Sentiment Classifica...

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International Conference on Data and Software Engineering (ICODSE)

作者： Matthew Martianus Henry Nur Adhianti Hervanto Mahmud Isnan Dian Kurnianingrum Chyntia Ika Ratnapuri Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Entrepreneurship Department Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506407

ISBN: (纸本)9798331506414

Sentiment analysis is crucial method in business intelligence to extract insights, which typically begin with sentiment classification. One of the latest frameworks for generating sentence embeddings for sentiment classification is LLM2Vec, which allows Transformer decoder-based models to generate sentence embeddings for text representation. Its capability is deemed language-agnostic, which, in this study, the framework is leveraged for Tokopedia tweet sentiment analysis to prove the claim. The base decoder models used in the LLM2Vec framework were Llama 3 8B, Llama 2 7B, Sheared Llama 1.3B, and Mistral 7B. Two BERT-based models, which are the Indonesian SBERT model and IndoBERT trained with the SimCSE approach, were employed as a comparison. The generated embeddings were classified using logistic regression, SVM, and MLP Classifier. Classifiers using embedding generated by LLM2Vec with Llama 3 8B and Mistral 7B achieves on-par performance with classifiers that utilize IndoBERT SimCSE embeddings, while classifiers using embeddings generated by LLM2Vec with Llama 2 7B and Sheared Llama 1.3B achieves much lower performance. Classifiers with Indonesian SBERT embeddings achieve the highest F1 score performance. Despite slightly lower performance, this study has proven the language-agnostic capability of LLM2Vec, especially with Llama 3 8B and Mistral 7B in colloquial Bahasa Indonesia sentiment analysis, since none of the base decoders were ever trained using the Bahasa Indonesia corpus.

关键词： Support vector machines Sentiment analysis Logistic regression Social networking (online) Blogs Transformers Encoding Decoding Business intelligence Software engineering

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Concept, Technology, Barriers To Smart Village: A Systematic Literature Review

Concept, Technology, Barriers To Smart Village: A Systematic...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Joy Nashar Utamajaya Meyliana Harjanto Prabowo Achmad Nizar Hidayanto Arief Ramadhan Computer Science Department BINUS Graduate Program - Computer Science Department Bina Nusantara University Jakarta Indonesia School of Computing Telkom University Bandung Indonesia

Smart villages that utilize digital technology are a solution to assist rural community services in meeting their needs, especially for developing countries. However, financial problems, namely the high cost of infrastructure, the size of the informal economy and governance are challenges in limiting the government’s aspirations regarding the smart village concept. The presentation of this article examines the state of smart village development in developing countries, which includes conceptual understanding, motivations, drivers and barriers to smart villages. The purpose of this study is to find answers to research questions by reviewing several selected study articles. The method used was to search for selected studies and there were 60 selected studies identified from a search of five literature databases which initially contained 3394 articles. The results of the data were analyzed using synthetic analysis and thematic analysis. The results of this study found data related to Concept, Technology, Barriers To Smart Village which came from several articles by answering questions from the research, namely RQ1: How many articles from the 10 most populous countries discussed Smart Village, RQ2: What are the basic dimensions of Smart Village, RQ3: What new technologies are discussed in Smart Village digitization, RQ4: What are the Challenges in Smart Village. The results of this SLR can also later be used as a reference for further researchers to find out the background of research related to smart villages. The conclusion obtained in this research is the end of the explanation of this article concludes that there are still many shortcomings in this research and it is hoped that in the future many studies will be able to explore other aspects such as regulations and others that are not discussed in the article so that it is expected to be a reference for further researchers to examine information related to smart villages. in order to find an ideal and up-to-date con

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Blockchain and API Development to Improve Relational Database Integrity and System Interoperability

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Procedia computer science 2023年 216卷 151-160页

作者： Andhika Naafi Ramadhan Kharisma Naufal Pane Kun Rifki Wardhana Suharjito Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia

Technological developments have resulted in a trend of cryptocurrencies that use a technology called blockchain to create and record all transactions made into a digital ledger. Along with the emergence of the trend of cryptocurrencies, this development has also resulted in crimes that hit the digital world, such as data leakage and cyber espionage. This threat can be prevented by applying blockchain technology to the database that has been used. Therefore, we need a system that can facilitate the use of blockchain technology and can process data from an existing relational database into a blockchain-based database. The system developed in this study was built with the FastAPI framework that uses the Python programming language and the React framework that uses the Javascript programming language. This system was tested using Katalon and Wireshark software to perform throughput testing and man-in-the-middle attacks. Evaluation of this system is assessed based on the average throughput time and also the results of Wireshark packet capture. The system designed in this research is expected to help overcome interoperability problems when using blockchain and improve relational database integrity. The results of the test show that the system is safe from man-in-the-middle attacks while sending data through API and has a faster throughput time than BigchainDB system by 4.151 seconds.

关键词： Blockchai Cybercrim Database Interoperability

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Analysis of ensemble majority voting approach for acute lymphoblastic leukemia detection using svm trained on white blood cell abnormalities in images 9th

Analysis of ensemble majority voting approach for acute lymp...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Januardo, Bryan Putradinata, Harley Moniaga, Jurike V. Nabiilah, Ghinaa Zain Computer Science Department Binus Graduate Program Jl. Raya Kb. Jeruk No.27 RT.1/RW.9 Kemanggisan Kec. Palmerah Kota Jakarta Barat Daerah Khusus Ibukota Jakarta11530 Indonesia

Leukemia is a cancer that attacks and infects white blood cells which can hinder the capability for someone with leukemia to fight infections, which may cause severe complications or even death. While Acute Lymphoblastic Leukemia is a certain type of leukemia that is the most prevalent childhood cancer. Detecting this disease is a repetitive activity that can take a lot of time and resources, meanwhile Acute Lymphoblastic Leukemia has a fast growth rate. In this study, we will try to classify leukemia cancer using machine learning based on the images of white blood cells provided. This method could provide early diagnosis and reduce the burden on hematologist-oncologist by optimizing the resources that are available. This research will use the ensemble classifier concept by combining several SVM models like linear, polynomial, and RBF. That have been trained, then combined into one singular ensemble model. By combining these models, we hope to improve the classification performance by minimizing the drawbacks of using certain SVM kernels. The results of this classification obtained an accuracy performance of 70.01%. © 2024 The Authors.

关键词： Lung cancer

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Jakarta Smart City Mobile Application for Problem Reporting

Jakarta Smart City Mobile Application for Problem Reporting

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2021 International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021

作者： Bongestu, Dejan Rivaldo Yappiter Warnars, Harco Leslie Hendric Spits Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara Univerisity Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728195377

This paper discusses the possibility of a better smart city implementation with the Jakarta Information App. Our App will be a one-stop go platform where people could access new information regarding the city live and instantaneously, the information contained is not just from an average news report, but people from social media or communities can also contribute in giving up to date news 24/7. In order to create this app, some processes are done to dive deeper into Jakarta's core infrastructure, the way of living, and the society behind the city. Jakarta Information App's goals are to connect the people everywhere at any time or place;it is not just an average social media app, its main objective is to be some hub for the city, it is an a2-way connected dots, the city with the people and also the reverse. The proposed system has been modeled with a use case diagram to design the business process and using the class diagram to model the database model diagram. The user interface has been designed as a means of communication between the user and the system. © 2021 IEEE.

关键词： Smart city

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