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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Jason Sebastian Sulistyawan Kuncahyo Setyo Nugroho Bens Pardamean Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

Many smoking-related diseases are difficult to treat and often fatal. Rather than treating diseased smokers, preventing the diseased is more achievable, though, many of them deny to being smokers, leading to another problem. Thus, this study aims to detect important aspects that can detect that the person is a smoker or not through their bio-signals through using SHAP, along with a comprehensive analysis of the used methods, gradient-boosting algorithms XGBoost, LightGBM, and CatBoost, known for their efficiency in handling complex datasets and non-linear relationships. The study then found that triglyceride, Gtp, hemoglobins significantly affect the body's responses to smoking, based on the CatBoosts’ results, having an AUC score of up to 0.8612 and an accuracy score of up to 0.7776 with the selected features.

关键词： Seminars Measurement Accuracy Predictive models Feature extraction Boosting Physiology Classification algorithms Reliability Diseases

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Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN)

Development of Detection Lung Disease Stand Alone System Bas...

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International Conference of computer and Informatics Engineering (IC2IE)

作者： Edgar Caesar Liewarnata Yosica Mariana Sofyan Tan Suryadiputra Liawatimena Winda Astuti Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Product Design Program Industrial Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification.

关键词： Training Accuracy Tuberculosis Pulmonary diseases Lungs Stethoscope Recording Convolutional neural networks Mel frequency cepstral coefficient Testing

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Hotel Information System Management Audit Using COBIT 2019 - APO12

Hotel Information System Management Audit Using COBIT 2019 -...

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Innovation in Technology (INOCON), IEEE International Conference for

作者： Joy Nashar Utamajaya Suhono Harso Supangat Ford Lumban Gaol Benny Ranti BINUS Graduate Program School of Information System BINUS University Jakarta Indonesia School of Electrical Engineering and Informatic Bandung Institute of Technology Bandung Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Depok Indonesia

In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company’s business goals. Given the large contribution of information technology in the application of hotel applications as a supporting information system, it is a vital system that must avoid risks that can hinder and cause harm to the hotel management business processes. Therefore, it is necessary to carry out risk management using the COBIT 5 framework to manage possible risks that may occur based on the APO12 (Manage Risk) domain. From the evaluation results of the data obtained through observation and interviews as well as the calculation of the results of the questionnaire based on 6 APO12 subdomains, the results of the risk management level capability assessment in hotel applications are still at level 3 or have reached the level of established process with the target to be achieved at level 4 resulting in a gap of 1 level. Based on the results obtained, it is necessary to propose recommendations that can be used by hotels in improving the application of information technology risk management so that in the future it can achieve the expected target level so that the APO12 level of capability can increase and become more optimal.

关键词： Technological innovation Companies Risk management Information technology Interviews Information systems

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Mobile Application to Help Abandoned Pets

Mobile Application to Help Abandoned Pets

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Blockchain and Distributed Systems Security (ICBDS), IEEE International Conference on

作者： Salicca Dewi Rahajeng Siti Julianingsih Nurfitriyani Zakin Izzani Akbar Calvin Leonardo Harco Leslie Hendric Spits Warnars Laurens Spits Warnars Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350354348

ISBN: (纸本)9798350354355

As social beings, humans like to interact with each other, including other creatures of God, such as animals, and keep them as pets. Many pets, such as dogs, cats, birds, fish, rabbits, and so on, include unusual pets such as reptiles, pigs, insects, etc. As a result of the lack of human awareness of pets and the nature of keeping animals, which is only for fun, it is not soulful to keep animals. So when people are bored, they abandon their pets, which causes new problems in human life today. In this case, we created a mobile application that can be shared with pet lovers where they can share information about abandoned pets and the possibility of owning pets from these abandoned pets. Mobile applications were designed using use case diagrams to show business processes, class diagrams to show database models, and user interfaces to present a similar interface to users. This mobile application will become a platform that can gather all people who care about pets and make pets a part of humans.

关键词： Rabbits Animals Insects Entertainment industry User interfaces Media Fish Mobile handsets Mobile applications Security

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An Integrated Mobile Vision System for Enhancing the Interaction of Blind and Low Vision Users with Their Surroundings

An Integrated Mobile Vision System for Enhancing the Interac...

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3rd International Conference on Image Processing and Vision Engineering, IMPROVE 2023

作者： Chen, Jin Ramnath, Satesh Samaroo, Tyron Maksakuli, Fani Ruci, Arber Sturdivant, E’edresha Zhu, Zhigang Nearabl Inc New YorkNY10023 United States Computer Science Department The City College of New York - CUNY New YorkNY10031 United States PhD Program in Computer Science The Graduate Center - CUNY New YorkNY10016 United States

ISBN: (纸本)9789897586422

This paper presents a mobile-based solution that integrates 3D vision and voice interaction to assist people who are blind or have low vision to explore and interact with their surroundings. The key components of the system are the two 3D vision modules: the 3D object detection module integrates a deep-learning based 2D object detector with ARKit-based point cloud generation, and an interest direction recognition module integrates hand/finger recognition and ARKit-based 3D direction estimation. The integrated system consists of a voice interface, a task scheduler, and an instruction generator. The voice interface contains a customized user request mapping module that maps the user’s input voice into one of the four primary system operation modes (exploration, search, navigation, and settings adjustment). The task scheduler coordinates with two web services that host the two vision modules to allocate resources for computation based on the user request and network connectivity strength. Finally, the instruction generator computes the corresponding instructions based on the user request and results from the two vision modules. The system is capable of running in real time on mobile devices. We have shown preliminary experimental results on the performance of the voice to user request mapping module and the two vision modules. © 2023 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Palmprint recognition

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A Design Study on Integrated Complex Coefficient Filters with Peripheral Circuits for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2025年第1期145卷 16-24页

作者： Shouno, Kazuhiro Sato, Lina Fukagawa, Kanta Tanimoto, Hiroshi Muto, Cosy Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan

This paper proposes a measurement technique for an integrated complex filter. The proposed method is based on two measurement methods with integrated circuitry for calibration. It is accomplished by applying square waves to an FUT (Filter Under Test) instead of sinusoidal waves or by superposing transfer characteristics obtained by applying a single sinusoidal wave to an FUT. In both of the above methods, the output signal connected to the external measurement equipment via a 50 Ω coaxial cable and so on. In this case, the output signal of the FUT should be amplified by internal or external amplifiers, which degrades the response. However, it is cancelled out by the proposed calibration circuitry with some analog switches. In addition to the above, for the RC polyphase filter, the source resistance and the load capacitance degrade the measurement results and their effect is discussed. The validity of the proposal is confirmed through computer simulation for a third-order RCPF whose passband is 8–40 MHz fabricated by Phenitec 0.6 µm CMOS process. It is shown that the measurement error is −1.10 dB for the square-wave method and −1.00 dB and −0.43 degrees for the superposition method at 40 MHz. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Capacitance

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Optimizing 3D Clothing Models for VR: A Deep Learning Approach to Triangle Count Reduction

Optimizing 3D Clothing Models for VR: A Deep Learning Approa...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Surasachai Doungtap Varinya Phanichraksaphong Jenq-Haur Wang International Graduate Program of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

This study presents a deep learning framework optimizing 3D clothing models for VR, using a CNN to significantly reduce the triangle count of models from DeepFashion3D and CAP-UDF datasets. Achieving a balance between efficiency and detail, it cuts triangle count from over 160,000 to below 4,000, maintaining high DPI. The approach automates optimization, promising scalability and efficiency in VR fashion, setting a foundation for future 3D content development, enhancing virtual garment realism and interactivity.

关键词： Deep learning Solid modeling Three-dimensional displays Scalability Clothing Optimization Consumer electronics

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Intelligent Decision Support System for Higher Education Institutions

Intelligent Decision Support System for Higher Education Ins...

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International Conference of Signal Processing and Intelligent Systems (ICSPIS)

作者： Nunik Afriliana Meyliana Ford Lumban Gaol Haryono Soeparno Computer Science Department Binus Graduate Program Computer Science Program Bina Nusantara University Jakarta Indonesia Information System Department School of Information System Bina Nusantara University Jakarta Indonesia

To ensure the sustainability of their operations, higher education institutions have to establish a robust strategic plan. Higher education institutions have an obligation to continuously assess the quality of their educational offerings in every program to comply with the standards established by the government and other educational entities. The implementation of intelligent decision support systems is a feasible approach among other techniques for addressing the aforementioned challenges. An intelligent decision support system has the potential to enable the business to uphold its adherence to regulations, enhance operational effectiveness, and optimize overall performance. This study aimed to determine the current state of intelligent decision support systems through the implementation of a comprehensive literature review. The second goal is to evaluate the best practices, methods, and implementation of intelligent decision support systems within higher education institutions. The findings indicate that intelligent decision support systems have the capacity to serve as a viable option for higher education, particularly in terms of enhancing the accuracy and efficiency of decision-making processes. Intelligent decision support systems exhibit a strong correlation with the fields of data mining and computational intelligence techniques. Nevertheless, the amount of research conducted on this subject is limited.

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Analyzing STEM Women’s Employability: A Machine Learning Framework with Clustering and Multi-Target Classification

Analyzing STEM Women’s Employability: A Machine Learning Fr...

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computer Sciences, Engineering, and Technology Innovation (ICoCSETI), International Conference on

作者： Nadzla Andrita Intan Ghayatrie Wina Permana Sari Devi Fitrianah Esyin Chew Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Cardiff School of Technology Cardiff Metropolitan University Cardiff United Kingdom

ISBN: (数字)9798331508616

ISBN: (纸本)9798331508623

The gender gap in Science, Technology, Engineering, and Mathematics (STEM) fields highlights significant research opportunities, particularly in examining the employability of female graduates. This study introduces a novel machine learning framework integrating Clustering and Multi-target Classification to analyze employment waiting time and job linearity among women STEM alumni. Using K-Means Clustering and Multi-Target Logistic Regression, the framework achieved a classification accuracy of 77% and a silhouette score of 0.61, demonstrating its effectiveness in predictive analysis. Beyond these results, the framework offers a robust methodology for integrating Clustering with Classification, enabling a nuanced understanding of the employability challenges faced by women in STEM. This approach identifies key patterns in employment data, paving the way for targeted interventions and actionable insights. Furthermore, the findings aim to inform data-driven policymaking and future research to improve employability outcomes. This work contributes to addressing systemic challenges and fostering gender diversity in STEM careers while enhancing opportunities for women.

关键词： Logistic regression Technological innovation Accuracy Computational modeling Employment Linearity Machine learning Predictive analytics STEM Gender issues

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Leveraging ChemBERTa Robustness in Drug-Drug Interaction Classification via Molecular Decomposition

Leveraging ChemBERTa Robustness in Drug-Drug Interaction Cla...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Christian Kenneth Alyssa Imani Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

Understanding drug-drug interactions (DDIs) can benefit us by enhancing drug effectiveness and preventing side effects that arise from consuming multiple drugs administered together. However, as the number of novel drugs increases, predicting potential DDIs becomes more challenging. Previous studies have used the molecular language model ChemBERTa to predict potential DDIs, but the predictions were only tested on unseen drugs and not dissimilar drugs, while also performing poorly. In this study, we demonstrate that a simple molecular preprocessing method using BRICS decomposition can enhance ChemBERTa robustness in predicting potential DDIs for unseen-dissimilar drugs. Specifically, we employ fragmentation with a minimum fragment size of 5 (BRICS-5), which balances the number of fragments and decomposition speed. Using this method, we were able to improve ChemBERTa robustness, reflected by an approximate increase of 1.5% in recall and 2.2% in the f1-score compared to non-decomposed molecules. Our findings suggest that this preprocessing method could be useful in the development of future AI-based approaches for solving challenging molecular tasks across different settings and various model architectures.

关键词： Drugs Seminars Accuracy Data preprocessing Predictive models Robustness Data models Intelligent systems Information technology

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