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Artificial Intelligence of Things (AIoT), IEEE Annual Congress on

作者： Nico Surantha David Jayaatmaja Sani Muhamad Isa Faculty of Science and Engineering Department of Electrical Electronics and Communication Engineering Tokyo City University Tokyo Japan Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350392296

ISBN: (纸本)9798350392302

The rapid development of Internet of Things (IoT) technology has enabled the widespread deployment of health monitoring systems. Traditionally, the health monitoring system has been limited by centralized processing and storage in the cloud, leading to latency issues and potential data loss. This paper introduces a smart sleep monitoring system based on edge computing, utilizing microservices architecture and caching techniques. The proposed system employs edge computing to enable data processing closer to the source, reducing latency and improving real-time monitoring capabilities. Caching is employed to reduce database load and optimize random access memory (RAM) usage. This research addresses latency and response time challenges on IoT health monitoring platforms in environments with poor network quality while optimizing database load and resource usage on Jetson Nano as the edge computing device. Using Electrocardiogram (ECG) data as input, the proposed system yields impressive performance metrics. The research results indicate that the proposed system can increase throughput by 26.92 KB/s, reduce response time by 18.8 ms, and decrease latency by 20.86 ms compared to the previous work. Message Queuing Telemetry Transport (MQTT) integration reduces CPU usage by approximately 40% and RAM usage by about 81.24%.

关键词： Cloud computing Databases Random access memory Microservice architectures Real-time systems Nanoscale devices Internet of Things

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Deep learning for oil palm fruit ripeness classification with densenet 6

Deep learning for oil palm fruit ripeness classification wit...

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6th International Conference on Information Management and Technology, ICIMTech 2021

作者： Herman, Herman Cenggoro, Tjeng Wawan Susanto, Albert Pardamean, Bens Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Program Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

Oil palm fruit farming is one of the most leading agriculture industries in the South East Asia region. Unfortunately, most of the harvesting method is still done through manual labor. Multiple research has been conducted to help farmers automatically detect the ripeness level of the oil palm fruit. We conducted an experiment of detecting the ripeness level of oil palm fruit by using one of the state-of-the-art computer vision approaches, which was deep learning with a Convolutional Neural Network (CNN). The dataset used consists of 7 levels of ripeness with 400 images of oil palm fruits. The models used in this test scenario were both AlexNet and DenseNet. The result of this study showed that DenseNet has been proven to outperform AlexNet by 8.5% in terms of accuracy and 8% in F1 score. © 2021 IEEE.

关键词： computer vision

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Machine Learning Approaches in Detecting Autism Spectrum Disorder

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Procedia computer science 2023年 227卷 1070-1076页

作者： Daniel Nicholas Dominic Tjeng Wawan Cenggoro Bens Pardamean Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

Early detection of Autism Spectrum Disorder (ASD) needs to be increased to prevent further adverse impacts. Thus, the classifi-cation between ASD and Typically Development (TD) individuals is an intriguing task. This review study has collected 26 related papers to answer four research questions, i.e., what are the most used data inputs, brain atlases, and machine learning models for ASD classification, as also to discover the significant parts of the brain correlated with the ASD. It was eventually found that functional connectivity matrix, Support Vector Machine, and CC200 are the most frequently used data input, model, and brain atlas, respectively. Researchers also concluded that the posterior temporal fusiform cortex, intracalcarine cortex, cuneal cortex, subcallosal cortex, occipital pole, and lateral occipital cortex are the brain regions highly correlated with ASD.

关键词： autism spectrum disorder brain atlas brain region machine learning

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Implementation of Lightweight PRNG on PLC for Industrial Control Systems 3

Implementation of Lightweight PRNG on PLC for Industrial Con...

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3rd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2023

作者： Sama, Andi Gaol, Ford Lumban Harso Supangkat, Suhono Ranti, Benny Binus Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Institute of Technology Bandung Faculty of Digital Communication and Hotel & Tourism Bandung Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9798350394559

The Information Technology/Operational Technology convergence towards Industry 4.0 opens the opportunity to leverage recent advancements in Information Technology for Operational Technology, such as Cloud, Internet of Things, and Artificial Intelligence. Meanwhile, cyber-attacks are increasing for Operational Technology. The security aspect in Operational Technology systems has traditionally been a low priority, in contrast with speed. This introduces challenges as Industrial Control Systems such as programmable Logic Controller in Operational Technology have been traditionally optimized for speed rather than security due to limited computing power. As computations need to be as efficient as possible, security in Operational Technology has yet to be managed as robustly as in Information Technology. Operational Technology communication protocols for securing data transfer, for example, have no or just a few security capabilities, even for basic authentication and encryption. Common security algorithms rely on random numbers. However, Random Number Generator is not usually part of standard functions in programmable Logic Controllers, the core control component in Industrial Control Systems. In Industrial Control Systems, the Random Number Generator is mostly implemented as a software-based Pseudo Random Number Generator. This paper shows how to apply a Pseudo Random Number Generator in a Siemens Compact PLC S7-1200 using a modified lightweight XORshift algorithm. The XORshift algorithm can generate better randomness than the system's clock-based implementation in the Siemens Library of Generic Functions. © 2023 IEEE.

关键词： Internet of things

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Low-Resolution Face Recognition for CCTV and Edge-Powered Smart Attendance Systems

Low-Resolution Face Recognition for CCTV and Edge-Powered Sm...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Nico Surantha Edward Yose Sani Muhamad Isa Department of Electrical Electronics and Communication Engineering Faculty of Science and Engineering Tokyo City University Tokyo Japan Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Attendance systems have become more modern, and one of the biometric systems without physical contact is face recognition. However, many face-based attendance systems still carry out attendance individually and cannot detect multiple faces simultaneously. In addition, capturing facial data in real-time is still a challenge because the relatively large distance between the camera and the individual reduces the ability to recognize faces. The general solution is to use super-resolution to generate better-quality faces while maintaining the main facial recognition features. One technique still being researched is super-resolution generative adversarial networks (SRGAN). SRGAN can enlarge the resolution of captured images and maintain image quality sufficient for face recognition. The attendance system can be easily integrated into edge devices such as the Jetson Nano. This paper proposes automatic and effective attendance systems with the super-resolution technique to detect and recognize faces in low-resolution input. The experimental results show that using face data capture with a resolution of 40 × 40 pixels and a four-fold magnification results in a resolution of 160 × 160 pixels. Combining Face SRGAN with FaceNet architecture as the basis of face recognition can achieve an accuracy rate of 78.19% and an F1-Score of 81.13% with an average processing time of 1.61 seconds per frame on a PC and 14.55 seconds per frame on a Jetson Nano at an average of face recognition per frame of as many as up to 8 faces simultaneously.

关键词： Support vector machines Image quality Accuracy Face recognition Image edge detection Superresolution Generative adversarial networks

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Synthetic Batik Pattern Generator Using Wasserstein Generative Adversarial Network with Gradient Penalty 6

Synthetic Batik Pattern Generator Using Wasserstein Generati...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Andriadi, Kus Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Binus Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Yogyakarta55281 Indonesia

ISBN: (纸本)9798350358346

Batik is an Indonesian world cultural heritage. Batik consists of many kinds of patterns depending on where the batik comes from, Batik-making techniques continue to develop along with technology development. Among the batik making techniques that are widely used are hand-written, stamping, and printing. Batik motifs have been widely used as research material, especially in the field of artificial intelligence. The diverse appearance of batik motifs has attracted many researchers to carry out research on making synthetic batik patterns, one of which uses a Generative Adversarial Network. This paper presents a synthetic batik pattern model based on the Wasserstein Generative Adversarial Network with Gradient Penalty. This model has been proven to create new synthetic batik patterns quite well and almost identical with images provided in the dataset, with the notes if the dataset provided is large. © 2023 IEEE.

关键词： Generative adversarial networks

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Enhancing Interoperability of Digital Twin in the Maintenance phase of Lifecycle 6

Enhancing Interoperability of Digital Twin in the Maintenanc...

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6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022

作者： Ariansyah, Dedy Pardamean, Bens Bina Nusantara University Bioinformatics and Data Science Research Centre Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350399615

In today's digitalization era, asset management has evolved following the rapid adoption of information systems and digital technologies. In the maintenance phase of the asset, Digital Twin (DT) emerges as an effective approach to improve failure recognition and structural damage prediction through DT-driven Prognostic and Health Monitoring (PHM). As a result, DT allows asset manager to proactively plan maintenance strategy to improve the availability of the assets. However, to reduce asset downtime in a cost-effective and time efficient manner, DT for maintenance phase needs to be integrated with other software systems that manage the provision of maintenance service and spare part such as computerized maintenance management system (CMMS) or Enterprise Resource Planning (ERP). Nevertheless, many of the developed DT in PHM were not equipped with semantic data model and hence, lacks interoperability with other systems (e.g., other DT or non-DT system) and limits the effective use of the DT. To qualify as an effective DT, it needs a semantical-enabled interface to connect with data and models from various domain to enable DT-driven decision-making. This paper leverages a rule-based ontology reasoning model to enhance DT interoperability with other maintenance software systems. The results depicts that the developed model paves a way for an effective use of DT-driven system in asset maintenance management. © 2022 IEEE.

关键词： CMMS Digital Twin ERP Maintenance Ontology

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The Influence of Digital Financial Literacy on Interest in Investing in the Capital Market of Millennial Generation Students 1

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4th International Conference on Inventive Computation and Information Technologies, ICICIT 2022

作者： Gaol, Ford Lumban Christopher Dermawan, Gerry Rafif, Muhammad Resnandya Rubianto, Rully Matsuo, Tokuro Doctor of Computer Science Binus Graduate Program Jakarta Indonesia School of Information System Bina Nusantara University Alam Sutera Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9789811974021

ISBN: (纸本)9789811974014

In today's environment, financial knowledge is vital and should be possessed by everyone. Numerous people are financially disadvantaged as a result of the COVID-19 pandemic. This serves as a reminder of the critical nature of financial investment in the future. However, many Indonesians, particularly students, are still unfamiliar with capital market investing. In reality, investing in the stock market can provide a variety of benefits, including financial security, capital appreciation, and passive income. Financial literacy concerns can result in a lack of financial awareness among pupils. Indeed, financial literacy is widely available online and can be accessed at any time and from any location. We employed a quantitative method with a non-experimental research design for this study. A questionnaire survey is used to obtain data. The goal of this study is to determine whether there is a correlation between student interest in capital market investment and their digital financial literacy. As a result, extensive action is required to increase student interest in the capital market, which is precisely what this study wants to do. According to our findings, students who have access to digital financial and investment information have increased their financial literacy and developed a greater interest in investing in the capital market. Individuals are also encouraged by social media trends to try their hand at investing in the stock market. Additionally, students prefer to invest in stocks and mutual funds over other investing options. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Investments

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The Effect of E-Commerce on Increasing Consumption Behavior During a Pandemic 4th

The Effect of E-Commerce on Increasing Consumption Behavior ...

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4th International Conference on Inventive Computation and Information Technologies, ICICIT 2022

作者： Gaol, Ford Lumban Tompunu, Sherina Gloria Larissa, Jessica Adine Wijaksana, Arista Prajnawira, Ferdianto Matsuo, Tokuro Binus Graduate Program—Doctor of Computer Science Jakarta Indonesia School of Information System Bina Nusantara University Alam Sutera Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789811974014

The rapid development of technology and ease of information today greatly affects all aspects of life. During the COVID-19 pandemic, technology played an important role in maintaining community activities continued smoothly despite being hampered by several health policies during the COVID-19 pandemic. Many phenomena develop with new technologies in several fields, one in the economic field is e-commerce. E-commerce is a site that makes it easier for buyers to get the goods desired by the community, as well as the various interesting promos that are the attractiveness of the community to constantly shop in e-commerce so that the community applies consumptive behavior. So that the problem that will be discussed in this study is the development of e-commerce technology that affects people’s behavior in shopping which tends to be consumptive and hedonic. The purpose of this study is to determine the impact or effect of the use of e-commerce on consumptive behavior during the pandemic period and provide an overview of the potential regarding e-commerce in the future. This research method is quantitative. The data collection technique used for this study is to use a questionnaire. Thus, this research is expected to minimize the negative impacts that can be caused by the increasing consumptive behavior of society during the pandemic and provide wise e-commerce use. The results of this study can be seen from calculations using a formula that respondents tend to be more extravagant during the pandemic and for future potential, respondents will certainly enjoy the convenience provided by e-commerce. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COVID-19

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The Social Media Implications on the Sales of Business Products 3

The Social Media Implications on the Sales of Business Produ...

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3rd International Conference on Smart Data Intelligence, ICSMDI 2023

作者： Jacia, Elvina Dyan, Gabriel Ifan, Amelia Gaol, Ford Lumban Matsuo, Tokuro Bina Nusantara University Alam Sutera Department of Information System Indonesia Binus Graduate Program-Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9781665464871

The use of technology nowadays does not feel strange. Everyday people who use technology for their daily needs, starting with each other, seeking knowledge, can even earn income by doing business using technology. Social media is a tool that can be used by people to become with each other by creating, sharing, and exchanging information virtually through a network. However, in the current era, the notion of social media is not only about exchanging information, but also to support business products. The problem is how to compete tightly in this modern era in increasing the selling value of business products. The positive impact of social media for sales in business products are huge such as, increase sales, increase product promotion, greater market distribution. On the other side, the negative impact also takes part such as, the more competitors, the products compete fiercely in the market. This research aims to identify more the impact of social media on sales of business products that focused on business, benefit, and factor. The research method that we used is quantitative which focuses on the number of samples of respondents to support the research results and the results are in the form of a graphic that shows the answers of the respondents to the questionnaire. © 2023 IEEE.

关键词： Sales

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