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2nd International Conference on Sciences and Technology Applications, ICOSTA 2020

作者： Fitriasari, N.S. Anzani, L. Widiyanto, K. Lukman Apriansyah, M.R. Setiawan, M.A. Asnawiah, L.P. Shafa, M.G. Marine Information System Study Program Universitas Pendidikan Indonesia Geography Study Program Universitas Indonesia

Knowledge repository is commonly used to store and manage explicit knowledge from knowledge worker. The development of internet of things (IoT) in Industry 4.0 enables the improvement of quality and quantity of knowledge repository. This study focuses on developing IoT-based knowledge repository as a means to support knowledge integration within The Marine information system study program. The study provides architectural designs of a knowledge repository that consists of 5 knowledge domains of marine information system and the design of IoT-based knowledge repository, both of which are based on reviews on relevant literatures and focus group discussion. The solution offered by the current study allows knowledge integration through Community of Practice as the provider and the user of the knowledge. © Published under licence by IOP Publishing Ltd.

关键词： Internet of things

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S-Shaped Versus V-Shaped Transfer Functions for Salp Swarm Algorithm in Sentiment Analysis Feature Selection Problem 2

S-Shaped Versus V-Shaped Transfer Functions for Salp Swarm A...

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2nd International Conference on Advanced Innovations in Smart Cities, ICAISC 2025

作者： Ajeng Kristiyanti, Dinar Hairul Umam, Akhmad Program Study of Information System Universitas Multimedia Nusantara Tangerang Indonesia Program Study of Communication Science Tanri Abeng University Jakarta Indonesia

ISBN: (纸本)9798331506995

This paper proposed an advanced method to enhance sentiment analysis (SA) for large-scale datasets. Given the complexity of SA, especially when dealing with high-dimensional data rich in features, effective feature selection (FS) becomes crucial to manage and reduce the data's dimensionality. Conventional machine learning techniques often fall short in this regard, highlighting the need for more sophisticated FS algorithms. In this study, we propose an improved bio-inspired optimization technique known as the Salp Swarm Algorithm (SSA) as a wrapper method for feature selection to enhance sentiment analysis of Indonesian-language tweets. Feature selection is inherently an NP-hard problem, making meta-heuristic algorithms like SSA a more efficient choice than exact methods. However, SSA typically faces challenges in terms of slow convergence, particularly in binary problems and large datasets. To address this, we introduce eight SSA variants, each employing S-shaped and V-shaped transfer functions to map the continuous search space into a discrete one, thus facilitating efficient feature selection. The proposed SSA-based approach is benchmarked against existing metaheuristic algorithms, including both Ant Lion Optimization (ALO) and Particle Swarm Optimization (PSO). Comparative experiments demonstrate that the enhanced SSA method outperforms both PSO and ALO, showing superior performance in terms of classification accuracy and processing time. Specifically, the experimental results reveal that the SSA combined with the V2-shaped transfer function achieved in just 5.16 seconds using the Support Vector Machine (SVM) classifier, with an accuracy of 89.76%. Similarly, the SSA integrated with the S1-shaped transfer function closely follows, completing the processing in 4.38 seconds with an accuracy of 89.43%. These findings indicate that the proposed SSA-based feature selection approach efficiently explores the feature space, selects the most informative features, and sig

关键词： Particle swarm optimization (PSO)

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IoT-based Knowledge Repository Design for Supporting Knowledge Integration within the Marine information system study program

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Journal of Physics: Conference Series 2021年第1期1811卷

作者： N S Fitriasari L Anzani K Widiyanto Lukman M R Apriansyah M A Setiawan L P Asnawiah M G Shafa Marine Information System Study Program of Universitas Pendidikan Indonesia Geography Study Program of Universitas Indonesia

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S-Shaped Versus V-Shaped Transfer Functions for Salp Swarm Algorithm in Sentiment Analysis Feature Selection Problem

S-Shaped Versus V-Shaped Transfer Functions for Salp Swarm A...

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Dinar Ajeng Kristiyanti Akhmad Hairul Umam Program Study of Information System Universitas Multimedia Nusantara Tangerang Indonesia Program Study of Communication Science Tanri Abeng University Jakarta Indonesia

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

关键词： Support vector machines Sentiment analysis Technological innovation Accuracy Machine learning algorithms Metaheuristics Transfer functions Feature extraction Space exploration Classification algorithms

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The development of web-based virtual learning on computer network courses in assisting distance learning process in the information system study program the open university

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AIP Conference Proceedings 2024年第1期3048卷

作者： Andri Suryadi Dian Nurdiana Dyah Paminta Rahayu Information System Study Program Faculty of Science and Technology Open University South Tangerang Indonesia Mathematics Study Program Faculty of Science and Technology Open University South Tangerang Indonesia

Learning process at the information systems study program in the Open University is independently performed and integrated with printed teaching materials that have been provided for students. However, printed teaching materials alone are not enough to assist the students to learn detachedly. Many students need additional explanations related to the contents of the printed teaching materials. Therefore, an interesting virtual application is required to assist the students to conveniently learn the printed teaching materials, anytime anywhere. The expectant application is a web-based virtual learning application, while the courses that would be presented in the form of web-based virtual learning are those requiring virtual explanation like computer network courses. In making this web-based virtual learning application, the researcher would use the SDLC (software development lifecycle) method. Prior to making the application, a design is required in which this design would be sent to the application developer. In this study, the results of the conducted design are an application design document that could be understood 100% by the developer, so that it could be used as a reference in developing this virtual learning application.

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Deep Learning for Cyber Security: Deephoax Detection 2

Deep Learning for Cyber Security: Deephoax Detection

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2nd International Conference on Advanced Innovations in Smart Cities, ICAISC 2025

作者： Yakub, Sy. Yuliani Wowor, Rivo Juicer Agustriawan, David Irmawati Kristiyanti, Dinar Ajeng Winarno, P.M. Hassan, Rosilah Mohamad, Roshayu Razzaq, Randy Zahran Universitas Multimedia Nusantara Department of Informatics Tangerang Indonesia Information System Study Program Universitas Multimedia Nusantara Tangerang Indonesia Universiti Kebangsaan Malaysia Selangor Malaysia College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Uin Sultan Maulana Hasanuddin Department of Informatics Banten Indonesia

ISBN: (纸本)9798331506995

The increasing prevalence of deep hoaxes, such as fake news and phishing schemes, poses a significant threat to cybersecurity, undermining trust and spreading misinformation. In Indonesia, surveys indicate that more than 60% of people exposed to hoax news believe that it is true, emphasizing the urgent need for robust detection methods. Traditional cybersecurity approaches often struggle to keep pace with the growing scale and sophistication of these attacks. To address this challenge, this research investigates the use of deep learning techniques, specifically focusing on text-based hoax detection in the Indonesian language. The study fine-tunes IndoBERT, a pretrained deep learning model optimized for Indonesian text, to enhance the accuracy and scalability of hoax detection. The IndoBERT model was trained on a balanced dataset of 29,552 articles, comprising both hoax and real news content, collected from the Mafindo API and Kaggle's Indonesia News Dataset. The model was fine-tuned using supervised learning and evaluated using several key metrics, including accuracy, F1-score, precision, and recall. The results demonstrate that IndoBERT outperforms existing state-of-the-art approaches, achieving an accuracy of 98.51%, an F1-score of 98.44%, and a precision of 98.23% on the test set. These results highlight the effectiveness of IndoBERT for hoax detection, which offers a scalable solution to improve cybersecurity defenses against deceptive content. This research contributes to the integration of advanced deep learning models into cybersecurity systems, addressing the evolving landscape of cyber threats. © 2025 IEEE.

关键词： Cyber attacks

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Machine Learning Stroke Prediction in Smart Healthcare:Integrating Fuzzy K-Nearest Neighbor and Artificial Neural Networks with Feature Selection Techniques

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Computers, Materials & Continua 2025年第3期82卷 5115-5134页

作者： Abdul Ahad Ira Puspitasari Jiangbin Zheng Shamsher Ullah Farhan Ullah Sheikh Tahir Bakhsh Ivan Miguel Pires Department Information System Study Program Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Software Northwestern Polytechnical UniversityXi’an710072China Research Center for Quantum Engineering Design Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Computer Science and Software Engineering Shenzhen UniversityShenzhen518061China Cybersecurity Center Prince Mohammad Bin Fahd University617Al JawharahKhobarDhahran34754Saudi Arabia Cardiff School of Technologies Cardiff Metropolitan UniversityWestern AvenueCardiffCF52YBUK Instituto de Telecomunicacoes Escola Superior de Tecnologia e Gestao de AguedaUniversidade de Aveiroágueda3750-127Portugal

This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and Best First Search(BFS).The study demonstrates that BFS significantly enhances the performance of both *** BFS preprocessing,the ANN model achieved an impressive accuracy of 97.5%,precision and recall of 97.5%,and an Receiver Operating Characteristics(ROC)area of 97.9%,outperforming the Chi-Square-based ANN,which recorded an accuracy of 91.4%.Similarly,the F-KNN model with BFS achieved an accuracy of 96.3%,precision and recall of 96.3%,and a Receiver Operating Characteristics(ROC)area of 96.2%,surpassing the performance of the Chi-Square F-KNN model,which showed an accuracy of 95%.These results highlight that BFS improves the ability to select the most relevant features,contributing to more reliable and accurate stroke *** findings underscore the importance of using advanced feature selection methods like BFS to enhance the performance of machine learning models in healthcare applications,leading to better stroke risk management and improved patient outcomes.

关键词： Fuzzy K-nearest neighbor artificial neural network accuracy precision recall F-measure Chi-Square best search first heart stroke

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Deep Learning for Cyber Security: Deephoax Detection

Deep Learning for Cyber Security: Deephoax Detection

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： SY. Yuliani Yakub Rivo Juicer Wowor David Agustriawan Irmawati Dinar Ajeng Kristiyanti P.M. Winarno Rosilah Hassan Roshayu Mohamad Randy Zahran Razzaq Department of Informatics Universitas Multimedia Nusantara Tangerang Indonesia Information System Study Program Universitas Multimedia Nusantara Tangerang Indonesia Center for Cyber Security (CYBER) Universiti Kebangsaan Malaysia Selangor Malaysia College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Department of Informatics UIN Sultan Maulana Hasanuddin Banten Indonesia

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

关键词： Deep learning Measurement Training Surveys Adaptation models Technological innovation Accuracy Computer security Fake news Videos

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Survival Analysis of Kasturi Tobacco Plants in Jember District using the Stratified Cox and Extended Cox Models

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MethodsX 2025年

作者： Angga Iryanto Pratama Dwi Rantini Ratih Ardiati Ningrum Arip Ramadan Fazidah Othman Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia Research Group of Data-Driven Decision Support System Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia Information System Study Program School of Industrial and System Engineering Telkom University Surabaya Campus Surabaya 60231 Indonesia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Malaysia

In 2022, tobacco was the top export commodity, generating $106.3 million in sales. East Java Province contributes significantly to Indonesia's tobacco production, with an annual output of 188.6 thousand tons. Jember Regency is the area in East Java Province which is a Kasturi tobacco cultivation area. The productivity of Kasturi tobacco continues to decrease due to several factors that can affect the survival of the tobacco. This study aims to analyze the survival of Kasturi tobacco by creating stratified Cox and extended Cox models in order to handle factors that cannot fulfill the proportional hazard assumption. Based on the results of the analysis, the stratified Cox model is the best model with AIC and BIC values of 798.108 and 805.5748 respectively, while the extended Cox has AIC and BIC values of 840.2186 and 850.1732 respectively. Variables that can significantly affect the survival of Kasturi tobacco are the variable concentration of ZA fertilizer, pesticide concentration. The addition of ZA fertilizer must be appropriate, because if excessive it can cause poisoning of tobacco plants. Likewise with pesticides, if excessive it will cause damage to the leaves. This policy can increase the productivity of Kasturi tobacco. Then, Jember Regency contributes greater export capacity. • This paper aims to determine the factors that affect the survival of Kasturi tobacco plants in Jember • By using the extended Cox model, the best one is obtained using the Heaviside function with AIC and BIC values of 840.2186 and 850.1732, respectively • The stratified Cox model is better than the extended Cox model, which has AIC and BIC values of 798.108 and 805.5748, respectively

关键词： Productive Agriculture Cox Proportional Hazard Stratified Cox Extended Cox Kasturi Tobacco

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information system Analysis and Design for Mobile-Based Homain Applications 1

Information System Analysis and Design for Mobile-Based Homa...

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1st International Conference on information system and information Technology, ICISIT 2022

作者： Ikhsan, Muhammad Alttha Santoso, Daffa Albaihaqi Ruchiyat, Fauzan Farrel Maulana Ongowarsito, Henkie Bina Nusantara University Information System Study Program-School of Information System Jakarta Indonesia

ISBN: (数字)9781665402002

ISBN: (纸本)9781665402002

Builders are workers with specific expertise in development. Community needs for workers with special skills to repair parts of homes remain difficult to find due to space and space constraints. In the current era of the Covid-19 pandemic, there are many people like construction workers who want to find work, and many people who need construction workers to repair parts of their homes but are not sure if construction workers are performing well or not well recruited by them. In this study, the authors propose an application to understand how construction workers can be found through an online application, and how potential clients can find suitable and trustworthy contractors. Smartphone users only need a smartphone and an internet connection to access this HoMain app. The purpose of this study is to design an online application for a mobile-based construction service ordering system to support the needs of the community and builders during construction work. With this app, people can easily order construction services based on online location. The HoMain application development method adopts the Rapid Application method, and the application development is relatively fast and efficient. © 2022 IEEE.

关键词： Smartphones

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