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4th IEEE International Conference of computer science and Information Technology, ICOSNIKOM 2022

作者： Ariwibowo, Suminar Girsang, Abba Suganda Diana Bina Nusantara University Binus Graduate Program-Master of Computer Science Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350399073

This paper aims to build hate speech text classification model by applying a combination of LSTM and FastText. The features of hate speech & non-hate speech, target hate speech, and categories of the hate speech. Dataset of those features taken from previous research by Okky Ibrohim. FastText word embeddings is used for formation of text vectors that will be used as input of the LSTM training model. The evaluation results obtained by getting the level of accuracy using confusion matrix. The accuracy value of text classification in this study is 83.52% on the classification of hate speech, 78.44% on the classification of target labels for hate speech, 82.75% on the classification of the label for category of hate speech. © 2022 IEEE.

关键词： Long short-term memory

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Integration of Government Regulations to Anticipate the Threat of Terrorism with Radioactive and Nuclear Technology 8

Integration of Government Regulations to Anticipate the Thre...

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8th IEEE International Conference on Computing, Engineering and Design, ICCED 2022

作者： Agustina, Mega Wijiyanti, Rika Mantoro, Teddy State Intelligence College Medical Intelligence Post-graduate Program Bogor Indonesia Sampoerna University and State Intelligence College Media-Tech Lab Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9781665453899

The development of science and technology is currently experiencing rapid progress, starting in the fields of energy, oil, non-destructive testing, health, agriculture, and other fields. The use of radioactive substances in the health sector is used for radiotherapy, nuclear medicine, and radiodiagnostics. The use of excess nuclear and radioactive substances can endanger living things and the environment. Monitoring and supervision of the use of these elements are very needed in order to avoid their utilization for non-peaceful purposes, such as terrorism. Nowadays, terrorist attacks in Indonesia began to evolve from the use of conventional explosives to the use of chemical, biological, radioactive, and nuclear materials. The data shows that during the period 2011-2019, there have been six attempted terror attacks using chemical, biological, radioactive, and nuclear elements. This paper examines the role of ministries/agencies in anticipating the use of nuclear and radioactive substances for terrorism. Based on the results of the library study, there are several ministries/agencies that have protocols for handling terrorism attacks that use chemical, biological, radioactive, and nuclear elements, but they are still sectoral. Therefore, it can be concluded that the integration of the regulations/protocols in handling terrorist attacks by using nuclear and radioactive elements are needed in order to increase the monitoring and supervision of the handling of radioactive waste. In addition, it is necessary to add the RPM tools to prevent the misuse of radioactive substances and nuclear materials by irresponsible parties. © 2022 IEEE.

关键词： Terrorism

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Fusion of Frequency Domain Features of Face and Iris Traits for Person Identification

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Journal of The Institution of Engineers (India): Series B 2021年第5期102卷 987-996页

作者： Kagawade, Vishwanath C. Angadi, Shanmukhappa A. Department of Computer Applications Basaveshwar Engineering College Bagalkot India Department of Computer Science and Engineering Centre for Post Graduate Studies VTU Belagavi India

In this study, we present a new approach for person recognition through feature level fusion of face and iris traits. The strength of the multimodal biometric system relies much more on the consistency to determine relevant features from the individual biometric traits and fusion technique employed for integration. Hence, this paper presents a new feature extraction approach for a face–iris multimodal biometric system. The face and iris feature extraction is performed by employing Polar Fast Fourier Transform to obtain textural information in diverse scales and orientations of the face and eye images. The Canonical Correlation Analysis method is employed to integrate face and iris traits features, which reduces the new feature vector length than the input feature vectors. The proposed approach is capable to obtain and improve the discriminative power for person recognition from multi-feature data of face and iris traits. The effectiveness of the proposed model is illustrated through the use of both artificial and genuine face and iris multimodal databases, along with comparisons involving existing state-of-the-art techniques. © 2021, The Institution of Engineers (India).

关键词： Feature extraction

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Exploring the Effect of Activation Function on Transformer Model Performance for Official Announcement Translator from Indonesian to Sundanese Languages

Exploring the Effect of Activation Function on Transformer M...

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2023 International Conference on computer science, Information Technology and Engineering, ICCoSITE 2023

作者： Wijanarko, Bambang Dwi Fitria Murad, Dina Heryadi, Yaya Tho, Cuk Hashimoto, Kiyota BINUS Online Learning Computer Science Department Jakarta11480 Indonesia BINUS Online Learning Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket Campus Phuket83120 Thailand

ISBN: (纸本)9798350320954

Automated language translation involving low-resource language has gained wide interest from many research communities in the past decade. One lesson learned from the past COVID-19 pandemic, particularly in Indonesia, is that many local Governments have to release regular public announcements to keep people following health protocol especially when they are in public areas. Many studies showed some evidence that rural people in Indonesia which covers a large proportion of Indonesia's population, feel more convenience receiving official announcements in their local language. However, translating official announcement from the national language to many local languages in Indonesia require many experienced bilingual translators and time. This paper presents exploration results in developing an automated language translator model to translate texts in Bahasa Indonesia to the Sundanese language. In particular, this study aims to explore the effect of ReLU, Sigmoid, and Tanh activation functions of the Vanilla Transformer Model on its translation performance. The experiment results showed that the activation function under study gives similar training accuracy (0.98). However, ReLU achieves better performance than Tanh in terms of validation accuracy, training loss, and validation loss. © 2023 IEEE.

关键词： Chemical activation

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A Technological Tool Applied in a Systematic Literature Review: Learning Mathematical Concepts by Students with Intellectual Disabilities

A Technological Tool Applied in a Systematic Literature Revi...

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International Symposium on computers in Education (SIIE)

作者： Elcio Pasolini Milli Edmar Reis Thiengo State Department of Education of Espirito Post-graduate Program in Science and Mathematics Education Santo Vitoria Brasil Post-graduate Program in Science and Mathematics Education Federal Institute of Espírito Santo Santo Vitoria Brasil

ISBN: (数字)9798350376616

ISBN: (纸本)9798350376623

This paper presents the results of a systematic literature review developed as part of a doctoral research project in science and Mathematics Education. It aims to profile national and international research using a technological tool called “Buscad“ to map work related to the learning of mathematical concepts by students with intellectual disabilities. It is qualitative in nature, highlighting contributions to the field of inclusive mathematics education, and takes as its theoretical and methodological assumptions the systematic review of literature related to the perspective of inclusive mathematics education. The research was carried out using search terms directly in the following databases: CAPES Theses and Dissertations Catalog (T&D); Brazilian Digital Library of Theses and Dissertations (BDTD); CAPES Periodicals Portal; Scientific Electronic Library Online (SCIELO); International Publisher science, Technology, Medicine (SPRINGER); Directory of Open Access Journals (DOAJ); Scopus; Web of science; science Direct; and Educational Resources Information Center (ERIC). The results point to opportunities for dialogue between Brazilian and international research, along with the need to articulate the refinement of diversified resources and instructional materials with the improvement of methodological processes along with socio-cultural discussions on inclusion and valuing diversity.

关键词： Systematics Reviews Open Access Databases Bibliographies Education Medical services

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A Systematic Literature Review of Deep Learning Application in Multiclass Anomaly Detection for Chest Medical Imaging 6

A Systematic Literature Review of Deep Learning Application ...

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6th International Conference on computer and Informatics Engineering, IC2IE 2023

作者： Philips Pardamean, Bens Elwirehardja, Gregorius Natanael Isnan, Mahmud Bina Nusantara University Binus Graduate Program - Master of Compuer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta Indonesia

ISBN: (纸本)9798350345162

Medical imaging abnormality detection is challenging, but deep learning approaches have shown promise. This paper reviews the current state of the art in deep learning approaches for detecting abnormalities in chest medical imaging. To discover the trends, opportunities, and challenges associated with this field, 18 studies were selected from Google Scholar based on their titles, abstracts, and contents for extensive review to answer two research questions. The study found that the National Institutes of Health (NIH) Chest X-ray 14 dataset is the most used dataset for this task. Most research uses a single-modal approach, considering only image data as input, with X-ray being the more popular instrument. There are 8 out of 18 studies leverage the transfer learning approach, with ResN et50 being the most popular network. MobileNetV2 has demonstrated competitive results compared to more robust networks. Preprocessing techniques such as image enhancement and data augmentation are leveraged by 61.1 % of the reviewed studies and are shown to improve model performance. © 2023 IEEE.

关键词： abnormality detection attention mechanisms chest x-ray CT images deep learning transfer learning

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Comparison of K-Nearest Neighbor and Support Vector Regression for Predicting Oil Palm Yield 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Pardamean, Bens Suparyanto, Teddy Sinaga, Gokma Sahat Tua Elwirehardja, Gregorius Natanael Firmansyah, Erick Ginting, Candra Mawandha, Hangger Gahara Putra, Dian Pratama Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program—Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Faculty of Agriculture Institute of Agriculture STIPER Yogyakarta55282 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

With the high demand for oil palm production, implementations of Machine Learning (ML) technologies to provide accurate predictions and recommendations to assist oil palm plantation management tasks have become beneficial, such as in predicting annual oil palm. However, different geographical and meteorological conditions may result in different scales of influence for each variable. In this research, K-Nearest Neighbors (KNN) and Support Vector Regression (SVR) were used in predicting oil palm yield based on data collected in Riau, Indonesia. Pearson’s correlation coefficient was also calculated in selecting the input features for the models, whereas normalization and standardization were used in scaling the data. By setting the minimum absolute correlation threshold to 0.1 and using standardization, both models managed to obtain more than 0.81 R2, with SVR obtaining the overall best performance with 0.8709 R2, 1.372 MAE, and 1.8025 RMSE without hyperparameter fine-tuning. It was also discovered that the oil palm yield in the previous year is the variable with the most influence in estimating oil palm yield in the current year, followed by the number of plants and soil types. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Machine learning

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Cancer Prediction using Clinical and Genomic Data Fusion: A Systematic Review 6

Cancer Prediction using Clinical and Genomic Data Fusion: A ...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Julian, Kelvin Nugroho, Kuncahyo Setyo Nirwantono, Rudi Pardamean, Bens Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798331539603

This systematic review provides a comprehensive overview of the methods used to integrate genomic and clinical data in cancer prediction. The review includes 19 studies across various cancers, including breast, colorectal, melanoma, lung, pancreatic, and thyroid. The studies employed different methods to combine genomic and clinical data, including weighted polygenic risk scores, genetic and non-genetic risk scores, and different machine learning algorithms. The results show significant improvements in model prediction performance accuracy across multiple studies. The review highlights the potential benefits of integrating genetic and phenotypic information to improve disease risk prediction models and inform personalized healthcare strategies. © 2024 IEEE.

关键词： Lung cancer

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Patient Data Security in Telemedicine Services from Data Misuse in Health Practice 8

Patient Data Security in Telemedicine Services from Data Mis...

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8th IEEE International Conference on Computing, Engineering and Design, ICCED 2022

作者： Yuninda, Sinka Puji Aga Pasma, Satriani Mantoro, Teddy State Intelligence College Medical Intelligence Post-graduate Program Bogor Indonesia Sampoerna University and State Intelligence College Media-Tech Lab Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9781665453899

Misuse of a person's data can be found anywhere because of a lack of knowledge about how to manage data and secure it properly. The rapid development of information technology, creates various activities easily, including in the health sector. In the field of health itself, there is a long-distance consultation using various applications that facilitate long-distance relationships between doctors and patients, known as telemedicine. However, the emergence of this development does not deny the existence of cybermedicine. Cyber medicine is the dissemination of clinical and non-clinical patient information that can be misused for personal gain that can harm others. This can be used in telemedicine, all online-based, so there is a possibility of data leakage. The authors want to examine the extent of data protection for patients who use telemedicine services. This study was conducted using a literature review method taken from articles related to telemedicine. Therefore, there is a need for regulations to provide legal protection for victims who experience theft of personal data by providing certainty in the management of data and information, especially the management of personal data. If the data is not managed properly and appropriately, it will lead to abuse and cybercriminal attacks. © 2022 IEEE.

关键词： Hospital data processing

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Video Quality Indicators for Video-Based Learning System in Higher Education 23

Video Quality Indicators for Video-Based Learning System in ...

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9th International Conference on Frontiers of Educational Technologies, ICFET 2023

作者： Zulkarnain, Novan Prabowo, Harjanto Gaol, Ford Lumban Isa, Sani Muhamad Computer Science Department BINUS Graduate Program Computer Science Information System Bina Nusantara University Indonesia Department School of Information System Bina Nusantara University Indonesia Management Department BINUS Business School Undergraduate Program Information System Department School of Information System Bina Nusantara University Indonesia

ISBN: (纸本)9798400707353

Higher education worldwide has adopted Video-Based Learning (VBL) over the past decade. They have tried to build a VBL system to improve services to students. However, the researcher's topic was not fully explored, especially in making the video itself. What features are mandatory and must be considered in making a video lecture to increase student engagement. A systematic review of the literature (SLR) is a way to identify these features. This study provides a critical analysis of the current research in VBL over the last five years (2017 - 2021). It presents a general trend examining 1336 journals and many literary works related to VBL design in Higher Education, selected through a stepwise process based on PRISMA Framework guidelines, using pre-defined selection criteria. We carefully selected 32 journals and found 22 features referring to the Lecture Video Design succession. © 2023 ACM.

关键词： Learning systems

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