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检索条件"机构=Information Technology Program Study"

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Comparative Analysis of Deep Learning Methods for Automated Diagnosis of Pulmonary Diseases from Chest X-Ray Images: A study Based on ICD-10 2

Comparative Analysis of Deep Learning Methods for Automated ...

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2nd International Conference on Data, information and Computing Science, CDICS 2024

作者： Wijayakusuma, I.G.N. Lanang Sudarma, Made Putra, I. Ketut Gede Darma Sudana, Oka Engineering Study Program Universitas Udayana Bukit Jimbaran Indonesia Electrical Engineering Study Program Universitas Indonesia Bukit Jimbaran Indonesia Information Technology Study Program Universitas Udayana Bukit Jimbaran Indonesia

ISBN: (纸本)9781643685762

This research delves into the comparative assessment of diverse deep learning architectures for the automated identification of pulmonary diseases in chest X-ray images, aligning with the diagnostic framework of the International Classification of Deseases, 10th Revision (ICD-10). The evaluated architectures encompass Convolutional Neural Network (CNN), MobileNetV2, DenseNet, VGG16, and InceptionV3. Through an extensive investigation conducted on a comprehensive dataset comprising 108,948 chest X-ray images, we scrutinize the performance metrics and diagnostic accuracy of each architecture. Notably, our findings reveal MobileNetV2 as the frontrunner, exhibiting an outstanding accuracy rate of 97% for Emphysema disease. This remarkable accuracy underscores the robustness and efficiency of MobileNetV2, even amidst large-scale diasets, positioning it as a promising solution for the automated detection of pulmonary ailments from medical imaging. Additionally, we analyze the computational efficiency and resource requirements of each architecture, providing insights into their practical applicability in real-world clinical settings. The implications of our study extend beyond technical benchmarks, offering valuable insights for healthcare practitioners, researchers, and developers working towards enhancing diagnostic processes in pulmonary healthcare. By elucidating the comparative strengths and limitations of various deep learning architectures, this research contributes to the advancement of computer-aided diagnosis systems, paving the way for more accurate and efficient detection of lung diseases from chest X-ray imaging data. © 2025 The Authors.

关键词： Lung cancer

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Aircraft Flight Schedule Announcement at Pionir Indonesian Airport Based on SMS Broadcast 1

Aircraft Flight Schedule Announcement at Pionir Indonesian A...

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1st International Conference of Adisutjipto on Aerospace Electrical Engineering and Informatics, ICAAEEI 2024

作者： Kusumaningrum, Anggraini Wahyu, Septian Sahal, Ahmad Pujiastuti, Asih Ayuningtyas, Astika Pratiwi, Elizabeth Anna Adisutjipto Institute of Aerospace Technology Informatics Study Program Yogyakarta Indonesia Adisutjipto College of Technology Informatic Engineering Department Yogyakarta Indonesia Respati University D3 Information Technology Study Program Faculty of Science and Technology Yogyakarta Indonesia Adisutjipto Institute of Aerospace Technology Aerospace Engineering Study Program Yogyakarta Indonesia

ISBN: (纸本)9798331507930

The design and construction of delivering announcements using a web-based SMS gateway aims to help overcome problems that often occur at pioneer airports;this is because when passengers want to travel, many passengers still arrive late to check-in, even though the passenger ticket has a notification for checking. -in 1 hour before Departure. If a flight's Departure is delayed or accelerated, passengers will only receive this information when they arrive at the airport, whereas if at the time the departure notification is delayed or accelerated, the passenger is still outside the airport or still on their way to the airport, as a result, they will definitely not receive the information. Testing voice announcements on parking, arrival, departure, delay, check-in, and waiting room services, as well as testing SMS broadcasts (30 user numbers and one airline), shows that the announcement application provides information through voice data recording and broadcasts SMS to passengers and families. Testing was carried out at Indonesian Pioner airport for 30 passengers for a week. The percentage of Ease of obtaining test voice information was 81.98%, and the percentage of Ease of obtaining broadcast SMS information was 83.1%. Implementing the announcement is feasible at pioneer airports with a percentage of 82.54%. © 2024 IEEE.

关键词： Text messaging

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Software Development Based on Sign Language Video Integration to Increase Accessibility of Port information for the Deaf in Sanur-Bali 10

Software Development Based on Sign Language Video Integratio...

引用

10th International Conference on Smart Computing and Communication, ICSCC 2024

作者： Indrashwara, Decky Cipta Dananjaya, Md. Wira Putra Fery Surya Tapa, I Gede Indra Kumara, I Nyoman Trisna Adhiswari Wedagama, Dewa Ayu Agus Ariana, I Komang Universitas Pendidikan Nasional Civil Engineering Study Program Denpasar Indonesia Universitas Pendidikan Nasional Technology Information Study Program Denpasar Indonesia Environmental Engineering Universitas Pendidikan Nasional Denpasar Indonesia

ISBN: (纸本)9798350363104

This research focuses on Sanur Harbor, an inter-island ferry port located in southern Bali. The majority of visitors to Sanur Harbor are tourists who want to travel to Nusa Penida Island. At this port, facilities are available in the form of a Public Address System (PAS) and information officers whose job is to provide information regarding the arrival and departure of ships. However, the effectiveness of this facility is limited for deaf people. Deaf people often have difficulty getting this information independently and often have to rely on manual assistance from officers. This research aims to develop software based on sign language video integration which aims to increase the accessibility of departure and arrival information at Sanur Harbor for deaf people in Bali. The software development method uses a user-centered design development approach which involves the stages of needs analysis, design, implementation, and evaluation. Sign language videos will be integrated into the software as a medium to convey important information about ship departure and arrival schedules, travel routes, pier names, fast boat names, and other important information to deaf users. Evaluation is carried out through user testing and collecting feedback from users regarding understandability, usability, and user satisfaction with the software being developed. It is hoped that the results of this research can make a positive contribution to increasing information accessibility for deaf people in Sanur Harbor and can become a basis for developing similar technology in other locations. © 2024 IEEE.

关键词： User centered design

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Precision Rice Vending Machine by Using Multiple Load Cell and IoT Based

Precision Rice Vending Machine by Using Multiple Load Cell a...

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2023 International Conference on Computer Science, information technology and Engineering, ICCoSITE 2023

作者： Yuliandoko, Herman Panduardi, Farisqi Lusi, Nuraini Wibowo, Sapto Politeknik Negeri Banyuwangi Information Technology Program Study Banyuwangi Indonesia Politeknik Negeri Banyuwangi Mechanical Engineering Program Study Banyuwangi Indonesia Politeknik Negeri Malang Electrical Engineering Program Study Malang Indonesia

ISBN: (纸本)9798350320954

Indonesia has the world's largest Muslim population, so the potential for Zakat, Infaq, and Sadaqah (ZIS) funding is enormous. The existence of ZIS in the current Covid-19 pandemic is of extreme importance, as issues such as economic crisis, social inequality, and the rise of dhuafa (poor) are becoming more and more visible. However, in the presence of coronavirus, ZIS has become more challenging to manage and distribute. Bans on gatherings, distancing rules, and other restrictions to prevent the spread of the coronavirus make ZIS more challenging to manage. Therefore, we need innovations to build bridges between people in need and supporters. The Internet of Things (IoT) is one system that can bridge this. In this system, IoT enables machine-to-machine communication and reduces human interaction. This research uses IoT to support Rice Vending Machine with high accuracy. The accuracy is achieved using five load cells and a good rice way-out valve mechanism. In previous machines using a single load cell or open the valve according to a certain time. Based on its test results analysis and MAPE values, we found the machine's accuracy facing obtained very well, and the website monitoring was also very effective. This research provides innovation in ZIS management and dramatically benefits society. © 2023 IEEE.

关键词： Internet of things

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Advancements in Deep Learning Optimization for Post-Earthquake Building Damage Detection A Systematic Review

Advancements in Deep Learning Optimization for Post-Earthqua...

引用

2024 International Conference on Advanced information Scientific Development, ICAISD 2024

作者： Sonang, Sahat Yuhandri, Y. Tajuddin, Muhammad Universitas Putra Indonesia Yptk Information Technology Study Program Padang Indonesia Universitas Bumigora Department of Computer Science Mataram Indonesia

ISBN: (纸本)9798350392036

This study conducts a systematic literature review (SLR) that focuses on optimizing deep-learning techniques for post-earthquake building damage detection. By employing the PRISMA protocol, this review aimed to collect, analyze, and summarize the findings of various studies published between 2014 and 2024. This research identifies and evaluates optimization methods such as hyperparameter tuning, transfer learning, and data augmentation, highlighting their effectiveness and implementation. Challenges such as data quality, computational costs, and model interpretability were also discussed. The findings indicate that while deep learning techniques significantly enhance the accuracy and efficiency of damage detection, further research is required to address existing challenges and improve model robustness in diverse earthquake scenarios. © 2024 IEEE.

关键词： Contrastive Learning

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Risk Management of Bank and FinTech Collaboration: A Phenomenological Research 6

Risk Management of Bank and FinTech Collaboration: A Phenome...

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

作者： Legowo, Mercurius Broto Sorongan, Fangky Antoneus Subanidja, Steph Institute of Perbanas Study Program of Information System Faculty of Information Technology Jakarta Indonesia Institute of Perbanas Study Program of Accounting Faculty of Economic and Business Jakarta Indonesia Post Graduate School Institute of Perbanas Program of Master of Management Jakarta Indonesia

ISBN: (纸本)9798350345162

Banking and Fintech are encouraged to collaborate to fill each other's deficiencies and further grow the digital economy. This collaboration will create benefits for both banks, Fintech, and customers. However, this collaboration also comes with risks. The Financial Services Authority has stated that several risk phenomena can occur in the collaboration of banks and Fintech. First, no law guarantees the protection and exchange of customer personal data. Second, the risk of customer data leakage. Third, the risk of cyberattacks. The fourth is the risk of outsourcing. This research aims to analyze the risk phenomenon of bank and fintech collaboration through the Enterprise Risk Management Framework approach. This study uses a phenomenological research approach, which is a study to study how individuals subjectively experience and give meaning to the phenomenon. Data analysis based on this phenomenon data uses qualitative methods involving banking and fintech practitioners. The results of this study describe the phenomenon of risks that occur in banking-fintech collaboration, as approached by the Enterprise Risk Management framework. Proper risk management will minimize risks when the Bank collaborates with FinTech. This study hopefully contributes to making brief policy recommendations on bank and fintech collaboration risk management for Indonesian financial regulators. © 2023 IEEE.

关键词： bank collaboration ERM framework fintech risk management

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Urgency Detection of Events Through Twitter Post: A Research Overview 4

Urgency Detection of Events Through Twitter Post: A Research...

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4th International Conference on Electrical Engineering and Computer Science, ICECOS 2024

作者： Edlim, Frederick William Edo, Gregorius Wiratama, Rangga Kurnia Putra Mahmudin, Riyan Solihin, Andi Ariyanto, Amelia Devi Putri Purwitasari, Diana Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia Widya Husada University Information Technology and Systems Study Program Semarang Indonesia

ISBN: (纸本)9798350368253

Indonesia is located in volatile Pacific fire ring and stands as one of the most global disaster-prone areas. The government and public are in constant vigilance of the potential threats. Social media generates large amounts of data from its users and is one of the prime candidates to be used as a disaster monitoring and response system. Several studies have demonstrated the effectiveness of using such an approach for developing disaster monitoring systems. but due to the number of messages generated, filtering is needed to extract useful information from the message. Hence, it's needed to detect an urgency from a message. This review, which was carried out following the PRISMA model, focused on the detection of the urgency of Indonesian Twitter during crisis events. From studies selected, several recommendations are suggested for future endeavor in this topic. Future systems are advised to employ three or four class schemes rather than binary class to gain more nuanced insights into tweet urgency. On-Event training and testing approaches are suitable for frequently occurring events, whereas out-of-event approaches offer broader applicability for real-world scenarios. Both machine learning and deep learning methods, including multimodal approaches, have demonstrated efficacy in urgency detection. Addressing pre-processing challenges, such as abbreviations and slang, is critical, and ensuring consistency in manually annotated data is essential. Additionally, the selection of appropriate word embeddings, such as fastText, IndoBERT, or crisis-specific embeddings, is crucial for achieving optimal model performance. © 2024 IEEE.

关键词： Tweets

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Web Browser Extension Development of Structured Query Language Injection Vulnerability Detection Using Long Short-Term Memory Algorithm 4

Web Browser Extension Development of Structured Query Langua...

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4th IEEE International Conference of Computer Science and information technology, ICOSNIKOM 2022

作者： Turnip, Togu Novriansyah Aruan, Hotma Siagian, Anita Lasmaria Siagian, Leonardo Institut Teknologi Del Information Technology Study Program Toba Indonesia

ISBN: (纸本)9798350399073

Structured Query Language Injection (SQLi) is a client-side application vulnerability that allows attackers to inject malicious SQL queries with harmful intents, including stealing sensitive information, bypassing authentication, and even executing illegal operations to cause more catastrophic damage to users on the web application. According to OWASP, the top 10 harmful attacks against web applications are SQL Injection attacks. Moreover, based on data reports from the UK's National Fraud Authority, SQL Injection is responsible for 97% of data exposures. Therefore, in order to prevent the SQL Injection attack, detection SQLi system is essential. The contribution of this research is securing web applications by developing a browser extension for Google Chrome using Long Short-Term Memory (LSTM), which is a unique kind of RNN algorithm capable of learning long-term dependencies like SQL Injection attacks. The results of the model will be deployed in static analysis in a browser extension, and the LSTM algorithm will learn to identify the URL that has to be injected into Damn Vulnerable Web Application (DVWA) as a sample-tested web application. Experimental results show that the proposed SQLi detection model based on the LSTM algorithm achieves an accuracy rate of 99.97%, which means that a reliable client-side can effectively detect whether the URL being accessed contains a SQLi attack or not. © 2022 IEEE.

关键词： Long short-term memory

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Finding the Best Techniques for Predicting Term Deposit Subscriptions (Case study UCI Machine Learning Dataset) 4

Finding the Best Techniques for Predicting Term Deposit Subs...

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4th International Conference on Sustainable Engineering and Creative Computing, ICSEC 2022

作者： Setiyani, Lila Indahsari, Ayu Rosalina Wansen, Tjong President University Master of Science Information Technology Study Program Bekasi Indonesia President University Informatics Study Program Bekasi Indonesia

ISBN: (纸本)9798350322002

Knowing a lot about attributes, such as bank client data, marketing campaigns, social and economic context, and so on, is necessary to predict which bank customers are likely to sign up for time deposits. The direct marketing campaigns dataset for the bank institution was made available by the UCI machine learning repository. This dataset had previously been used in studies to forecast customers who would sign up for time deposits, but the outcomes of the two studies were different. The purpose of this study is to determine which machine learning methods are most effective for predicting customers who will sign up for time deposits. In this study, researchers used machine learning methods like random forests, K-nearest neighbors, decision trees, naive bayes, logistic regression, SVM, and XGBoost to uncover the truth. Results showed that XGBoost had the highest accuracy (91.73%), followed by the DT classifier (88.79%), LR classifier (91.2%), NB classifier (84.78%), KNN classifier (90.6%), SVM (89.6%), and XGBoost (91.44%). © 2022 IEEE.

关键词： Forecasting

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Monitoring System of Greenhouse Based on WSN and Auto Flushing Sensor Mechanism 6

Monitoring System of Greenhouse Based on WSN and Auto Flushi...

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6th International Conference on information technology, information Systems and Electrical Engineering, ICITISEE 2022

作者： Yuliandoko, Herman Panduardi, Farisqi Holik, Abdul Politeknik Negeri Banyuwangi Information Technology Program Study Banyuwangi Indonesia Politeknik Negeri Banyuwangi Agrobusiness Program Study Banyuwangi Indonesia

ISBN: (纸本)9798350399615

Indonesia is an agricultural country with agriculture as one of the mainstays of state income. However, the competition for agricultural production is currently very high, so it requires innovations in agricultural technology to increase the competitiveness of Indonesian food production. One of the latest agriculture technologies is Greenhouse. With Greenhouse, it is possible to adjust temperature conditions, room humidity and other plant parameters. In Indonesia, this technology has begun to be widely used but is still very limited due to technological constraints and high costs. In a greenhouse, some tools monitor plant parameters to support plant growth, such as water pumps, sensors, dynamos, and sprays. However, currently, there are still many greenhouses that operate these tools conventionally. This causes greenhouse operations to take a long time and a lot of labor, so greenhouse operations are expensive and complicated. Therefore, Greenhouse innovation is needed with a flexible, easy and efficient system. In this research, innovation will be carried out with a Greenhouse monitoring system by implementing the WSN (Wireless Sensor Network). In addition, the use of sensors with auto flushing is done to prevent encrustation on the sensor surface. Using WSN will increase the flexibility of data transmission and minimize energy use so that it can be applied in remote areas. Room temperature is also connected with a blower as an automation mechanism to maintain wind circulation in Greenhouse. The monitoring of plan nutrition in the Greenhouse is very important that why this research also study it. © 2022 IEEE.

关键词： Flushing Greenhouse Monitoring Sensor WSN

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