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4th International Conference on Electronics, Biomedical Engineering, and Health Informatics, ICEBEHI 2023

作者： Maulana, Fairuz Iqbal Lestari, Dian Adi, Puput Dani Prasetyo Arifin, Mohammad Nazir Purnomo, Agung Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Faculty of Medicine Universitas Airlangga Surabaya60132 Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta11480 Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789819714629

The field of the Internet of Medical Things (IoMT) is experiencing significant growth as it involves the integration of medical devices and systems with the internet and various digital technologies. This study provides a bibliometric analysis of scholarly articles pertaining to the Internet of Medical Things (IoMT) during the time frame of 2018 to 2022. The analysis is conducted using data sourced from the Scopus database. A total of 1165 documents were identified and analyzed to gain insights into the current state of research in this field. The analysis includes trends in publication output, top authors and institutions, and key research topics. The results of the analysis indicate a steady increase in publication output on IoMT over the past five years, with the highest number of publications in 2022. The top authors in this field were Mohanty, S.P., Kougianos, E., and Pirbhulal, S., while the top institutions were King Saud University, Chinese Academy of sciences, and University of North Texas. Co-citation analysis revealed that wearable devices, telemedicine, and data analytics were among the key research topics in IoMT. This bibliometric analysis offers useful insights into the present research landscape of the Internet of Medical Things (IoMT) spanning the years 2018 to 2022. The findings can be beneficial for researchers, practitioners, policymakers, and funding agencies in understanding the trends and priorities in this field. The top authors and institutions identified in this analysis can serve as valuable resources for collaboration and staying updated on the latest developments in IoMT. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Digital devices

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Web Development of Direct-to-consumer Genetics Testing 4

Web Development of Direct-to-consumer Genetics Testing

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4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Azizatikarna, Kians Parung, Deby Erina Amirullah, Dian Hidayat, Alam Ahmad Cenggoro, Tjeng Wawan Budiarto, Arif Simon Pardamean, Bens Genetics Indonesia Jakarta12940 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665453950

As the cost of genetic testing becomes more affordable each year, direct-to-customer (DTC) genetic testing services witness rapid market growth. This has encouraged the development of an easy-to-use website application to optimize potential customers to obtain informed choice regarding the offered DTC genetic testing as well as purchasing information. We present a wireframing process as a part of the agile software development process to build a web portal prototype for an Indonesia-based genetic testing service called DNAku. The approach in building the prototype used in this case is a part of the Agile Software Development Method. In brief, the wireframing stage resulted in this work consists of three main important outcomes. The first one is the use case diagram as a blueprint of this web-based system. A site map is then proposed as an extended version of the use case diagram which visualizes the whole pages with the links. Finally, based on this site map a series of page mock-ups are designed using Hyper Text Marking Language (HTML) and Cascading Style Sheets (CSS). The result of the prototype can be used as the basis for the next development stage, which is the coding stage based on the collected feedback from users. Considering the continuous application development via the wireframing method by taking into account the cycle of feedbacks from involved parties, this approach can strengthen the infrastructure to sustain DTC genetic business model, which has a niche market in Indonesia. © 2022 IEEE.

关键词： Sales

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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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Dagang Yuk Yuk As Smartphone Application for MSME Product Sales 2

Dagang Yuk Yuk As Smartphone Application for MSME Product Sa...

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Erinda, Muhammad Fandi Warnars, Harco Leslie Hendric Spits Sumardin, Winters Arianto, Jimmy Vinarycha, Devi Wahyu Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara Univesity Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665400527

Many MSMEs manually close their businesses in today's competition, especially those caused by the COVID19 pandemic, and besides that, the lack of technology implementation is even more aggravating. Like it or not, Micro, Small, and Medium Enterprises (MSMEs) must equip their businesses with the application of technology, and unfortunately, there are still many MSMEs that have not been able to take advantage of the benefits of technological developments. Many companies see this condition as an opportunity;for example, Gojek and Grab partner with MSME players to make it easier to trade their products or services. In this paper, a smartphone application for MSMEs called 'Dagang Yuk Yuk, ' which consists of activities such as Login, Create Order, Input Delivery Location, Select Courier, and Select Payment Method has been proposed. Dagang Yuk Yuk tries to give different ideas for implementing MSME actors where this application is only for MSME players as part of an MSME business unit. This paper discusses the application's design using use case diagrams to describe the business process, while class diagrams model the database design. This application was developed using Arduino studio and MySQL database for database storage. © 2022 IEEE.

关键词： Competition

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Evaluation of Machine Learning on Smart Home Data for Prediction of Electrical Energy Consumption

Evaluation of Machine Learning on Smart Home Data for Predic...

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

作者： Mochammad Haldi Widianto Alexander Agung Santoso Gunawan Yaya Heryadi Widodo Budiharto Computer Science Department BINUS Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Electrical energy consumption is always increasing, and this causes the supply of electrical energy to be increased to compensate. One solution is to predict electricity energy consumption using Artificial Intelligence (AI) technology in Smart Homes. Several studies' solutions for predicting electrical energy consumption usually focused only on performance but rarely evaluated Machine Learning (ML) by correlation for feature selection and utilized interpretability model. This study uses an ML model for predicting utilization (Linear Regression, Decision Tree, Random Forest, and XGBoost). Then, Feature Selection utilizes correlation to choose the best feature. After that, the interpretability model utilizes Local Interpretable Model-agnostic Explanations (LIME). The results show that XGBoost has the best Root Mean Squared Error (RMSE) value (0.318) with a percentage of the number of train and test data (90/10). After that, by eliminating features that correlate with 0.01, XGBoost improves with an increase of (0.018) to become (0.3). Then from LIME. This work also gets positive feature from XGBoost such as: "Furnance, Well dan Living Room".

关键词： Energy consumption Correlation Linear regression Smart homes Predictive models Feature extraction Data models

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Intelligent Digital Enterprise Architecture: Perspectives, Trends, and Technologies 9

Intelligent Digital Enterprise Architecture: Perspectives, T...

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9th International Conference on ICT for Smart Society, ICISS 2022

作者： Afriliana, Nunik Gaol, Ford Lumban Supangkat, Suhono Harso Ranti, Benny Computer Science Bina Nusantara University Computer Science Department Binus Graduate Program Jakarta11480 Indonesia Smart Cities and Communities Innovation Center Institut Teknologi Bandung Bandung40312 Indonesia

ISBN: (数字)9781665471350

ISBN: (纸本)9781665471350

Nowadays, many companies, industries, and organizations deal with digital disruption issues. They have to deal with it and take the initiative properly to keep their sustainability. Initiating a digital transformation by creating intelligent digital systems is one of many initiatives that could be considered to overcome these issues. Developing an intelligent digital system will maintain a company's performance, efficiency, and compliance. Numerous organizations are willing to create an intelligent digital system for their governance. However, they do not have sufficient knowledge on how to do it, including its enterprise architecture. Knowledge of enterprise architecture is an important part of properly developing an intelligent digital system. This research aimed to conduct a literature review to determine the perspective of the enterprise architecture model in intelligent digital system development. The second goal is to find recent trends and technology in intelligent digital enterprise architecture. Theoretically, it gives a contribution to providing a new perspective of more intelligent Enterprise Architecture with its trends and technologies compared to the old paradigm. Practically, it will contribute to providing an overview of how an enterprise could align the IT and business perspectives in building an intelligent enterprise with its cognitive characteristics © 2022 IEEE.

关键词： Architecture Digital transformation Bibliographies Buildings Companies Market research Sustainable development

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Mobile Application for Children to Learn BISINDO Sign Language

Mobile Application for Children to Learn BISINDO Sign Langua...

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International Conference on Inventive Computation Technologies (ICICT)

作者： Raynaldo Andreas Sarah Maria Alexander Khrisna Satyadhama Harco Leslie Hendric Spits Warnars Arief Ramadhan Maybin K. Muyeba Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Telkom University Bandung Indonesia MIST Consulting Manchester United Kingdom

Sign language is the most commonly used communication medium for people who are deaf and mute. By using body movements, they can convey meaning through visual cues, not vocal cues. This type of language is learned almost exdusively by people who are deaf or dumb and those who interact with them on a daily basis. Most people do not learn it because sign language is not part of basic education, and the lack of need to use it, especially from a young age. Most of the spoken languages in the world usually have sign language variants according to the language of their respective countries. In this study, a mobile application is developed for children to learn Indonesian sign language where the process model is designed using use case diagrams, and the database design is modeled with class diagrams. As for the implementation, the Android Studio software is used for the application, and the MySQLdatabase is for database storage.

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Indonesian Automatic Speech Recognition with XLSR-53

arXiv

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arXiv 2023年

作者： Arisaputra, Panji Zahra, Amalia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

This study focuses on the development of Indonesian Automatic Speech Recognition (ASR) using the XLSR-53 pre-trained model, the XLSR stands for cross-lingual speech representations. The use of this XLSR-53 pre-trained model is to significantly reduce the amount of training data in non-English languages required to achieve a competitive Word Error Rate (WER). The total amount of data used in this study is 24 hours, 18 minutes, and 1 second: (1) TITML-IDN 14 hours and 31 minutes;(2) Magic Data 3 hours and 33 minutes;and (3) Common Voice 6 hours, 14 minutes, and 1 second. With a WER of 20%, the model built in this study can compete with similar models using the Common Voice dataset split test. WER can be decreased by around 8% using a language model, resulted in WER from 20% to 12%. Thus, the results of this study have succeeded in perfecting previous research in contributing to the creation of a better Indonesian ASR with a smaller amount of data. © 2023, CC BY-SA.

关键词： Statistical tests

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Enhancing Efficiency in Yolov8n for Real-Time Detection of Oil Palm Fruits in Plantations Using Mobileone and Cross-Fusion

SSRN

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SSRN 2024年

作者： Hugo, Gregory Mushlik, Muhammad Suharjito Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia

Accurate detection of fresh fruit bunches (FFB) ripeness in complex plantation environments is challenging due to occlusion, varying lighting, intricate visual features, and limited computational resources of mobile devices. To address this, a resource-efficient, real-time detection system was developed using an optimized YOLOv8n model. The model integrates MobileOne modules and Cross-Fusion blocks to enhance efficiency without compromising accuracy. Specifically, Conv and C2f modules were replaced with MobileOne modules, reducing parameters by 85% and 81%, respectively. Cross-Fusion improved feature fusion, and its combination with MobileOne (CF-MobileOne) achieved a 51% reduction in parameters while maintaining performance. The dataset comprised images from videos captured in plantations, annotated into five maturity stages: flower, unripe, underripe, ripe, and abnormal, and underwent augmentation with class balancing through manual undersampling. The model outperformed baseline YOLOv8 variants and heavier models like YOLOv9c and Faster R-CNN, achieving an mAP50 of 0.795 and an inference speed of 140.57 FPS. Hyperparameter tuning with a batch size of 64, SGD optimizer, and a learning rate of 0.01 yielded optimal results. Despite challenges in detecting certain classes due to visual similarities and environmental variations, the system effectively enhances productivity and efficiency in precision agriculture for the palm oil industry. © 2024, The Authors. All rights reserved.

关键词： Fruits

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Data Mining for the Global Multiplex Weekly Average Income Analysis

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Procedia computer science 2023年 219卷 52-59页

作者： Nicholas Dominic Gregorius Natanael Elwirehardja Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

The box office (BO) income had significantly declined up to 80% in 2020, as the COVID-19 pandemic emerged. To minimize further financial risks, multiplex (multiple cinema complexes) owners need to analyze their potential income for each movie, each week. Therefore, we developed a proper data mining strategy that allows multiplex owners to analyze and discover insights on how successfully produced movies could be. The methodology comprises (1) data loading and exploration, (2) data cleaning, (3) data selection, integration, and transformation using Pentaho, (4) data mining in which the results were stored in the MySQL database, and (5) pattern evaluation and presentation using Qlik Sense as the Business Intelligence (BI) dashboard. Based on our data mining methodology, we revealed that drama, comedy, action, and thriller are favorite genres. We also found that DreamWorks Animation and Pixar Animation Studios are both the most popular production houses, even Apatow Productions and Escape Artists still have the biggest revenue on average.

关键词： movie multiplex income data mining Business Intelligence dashboard

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