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检索条件"机构=Postgraduate Program in Computer science"

共 267 条记录，以下是31-40 订阅

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Information Retrieval System to Find Articles and Clauses in UUD 1945 Using Vector Space Model Method 1

Information Retrieval System to Find Articles and Clauses in...

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1st Bukittinggi International Conference on Education, BICED 2019

作者： Sulaeman, O.R. Gata, W. Wahyudi, E. Hakim, M.J. Subandi, R. Setiyawan, R. Pratama, B. Master of Computer Science Postgraduate Program STMIK Nusa Mandiri Indonesia Graduate School Master's Degree Computer Science STMIK Nusa Mandiri Indonesia

This study aims to find articles and clauses from the 1945 Constitution (UUD 1945) using the Vector Space Model method that calculates the similarity of many documents. One document is represented by one clause from each article of the 1945 Constitution. The next step is pre-processing by deleting unnecessary words (stopwords) and changing it into basic words (stemmer) in the Indonesian language. Each document will be indexed to speed up query and simplify the weighting. Words weighting in documents is performed using the TF-IDF (Term Frequency-Inverse Document Frequency) algorithm by calculating the frequency of words in documents and all documents. The document search results will be presented in the ranking with the largest number of scoring appears at the top (descend sorting). The word search in this system more or less takes 90-100 milliseconds in 73 documents. © Published under licence by IOP Publishing Ltd.

关键词： Vector spaces

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Iota vs. Ripple: A Comparison Inside An Economy of Things Architecture for Industry 4.0 6

Iota vs. Ripple: A Comparison Inside An Economy of Things Ar...

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6th IEEE World Forum on Internet of Things, WF-IoT 2020

作者： Agostinho, Bruno MacHado Pereira, Mateus Manoel Back, Alexandre Pereira Sandro Roschildt Pinto, Alex Ribeiro Dantas, Mario Antonio Federal University of Santa Catarina Computer Science Postgraduate Program Florianópolis SC Brazil Federal University of Santa Catarina Florianópolis SC Brazil Federal University of Juiz de Fora Computer Science Postgraduate Program Juiz de Fora MG Brazil

ISBN: (数字)9781728155036

ISBN: (纸本)9781728155036

The increase of the number and different types of devices within the Internet of Things context and the emergence of cryptocurrencies are bringing challenges, opportunities, and changes. How these technologies will impact the current business and economic models are still unknown. This work proposes an architecture aiming to use these new opportunities to enable the M2M interaction for Industry 4.0. Our work, used as base the novel paradigm called Economy of Things, focused on how to digitalize, monetize, and exchange assets inside the IoT context. An experimental environment was designed to explore and compare the characteristics of the cryptocurrencies Ripple and Iota. The initial results showed the Iota transaction time 9143% slower than Ripple and finished with a difference of 3707%. Also, while Ripple did not present transaction errors, in the last test configuration Iota had 4.3% of unconfirmed transactions, and 14.3% of requests needed to be resent. Although the Ripple network charges some fees, the cost to do 18,600 transactions was USD 0.05490. We considered it a small price to pay for a more stable network. © 2020 IEEE.

关键词： Industry 4.0

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Interactive Multimedia Kolb Experiential Learning Model Using Logistic Regression Algorithm to Improve Student Cognitive

Interactive Multimedia Kolb Experiential Learning Model Usin...

引用

7th International Conference on Advances in Visual Informatics, IVIC 2021

作者： Khoirunnisa, Azizah Nurul Munir Rasim Rahman, Eka Fitrajaya Dewi, Laksmi Curriculum Development Study Program School of Postgraduate Studies Indonesia University of Education Bandung Indonesia Computer Science Education Study Program Department of Computer Science Education Indonesia University of Education Bandung Indonesia

ISBN: (纸本)9783030902346

The differences of each student become a challenge for educators in delivering learning materials. More often than not, students often find it difficult to process study materials. Conventional study-based learning may not always have a profound impact on students. Consideration of interactive multimedia as a tool for student-centered learning has not been widely discussed in scientific research. In this paper, the authors investigate interactive multimedia using Kolb’s experiential learning model in improving students’ cognitive abilities. This study uses a pre-experimental method and one-group pre-and post-test design type with the research population in class XI RPL and a sample of SMK students in Bandung. The results show that the application of interactive multimedia using Kolb’s experiential learning model is effective in improving students’ cognitive abilities. On the other hand, it is found that combining abstract learning materials with interactive visuals and activities that involve students’ participation could create exceptionally positive feedback from students. © 2021, Springer Nature Switzerland AG.

关键词： Students

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Comparison of naive bayes and K-NN method on tuition fee payment overdue prediction 4

Comparison of naive bayes and K-NN method on tuition fee pay...

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4th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2019

作者： Kusrini, Kusrini Luthfi, Emha Taufiq Muqorobin, Muqorobin Abdullah, Robi Wariyanto Universitas AMIKOM Yogyakarta Postgraduate Program Yogyakarta Indonesia Universitas AMIKOM Yogyakarta Computer Science Faculty Yogyakarta Indonesia

ISBN: (纸本)9781728151182

Attending basic education is an obligation for all Indonesian citizens. The financial cost is one of the input components to implement an education or even can be considered as the main requirement in achieving the goal of education. For a private education institution in Indonesia, the financial cost is mainly covered by students' tuition payments. SMK Al-Islam Surakarta is a private school that manages all its students to pay school tuition fees monthly. According to its last year's administrative report, the number of students who are late in paying school tuition fee is around 60%. Since the school's operational costs are heavily depended on their income from tuition fees, this considered an essential problem and has to be managed and predicted as well. This research will discuss techniques in predicting the late payment of tuition fees. From many popular methods available in this area, we observed two of them namely Naive Bayes and K-Nearest Neighbor (K-NN). This study will compare the accuracy between those two methods. The data used for the lab work is the official education basic data of Al-Islam Surakarta Vocational School in 2017/2018 totaling 236 data. To increase its accuracy, this study also combines the prediction methods with feature selection technique Information Gain which is commonly used to select an optimal parameter for the prediction process. In the end, the system is tested using the Confusion Matrix method. The results showed that the Naive Bayes Method with Information Gain attribute selection produced the highest accuracy of 69%. © 2019 IEEE.

关键词： Forecasting

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Towards disaster management in Indonesia Case studies: Jakarta and Yogyakarta provinces 5

Towards disaster management in Indonesia Case studies: Jakar...

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5th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2012

作者： Intarti, Yuni Reti Fitrinitia, Irene Sondang Widyanto, Muhammad Rahmat Urban Studies Postgraduate Program Universitas Indonesia Jakarta Indonesia Faculty of Computer Science Universitas Indonesia Jakarta Indonesia

Indonesia is a country straddling the equator line setting off a tropical climate, characterized by heavy rainfall, high temperatures, high humidity but low winds. It is also located in Southeast Asia, with a huge archipelago with total land and sea area reaching to about 5 million km2, comprised of more than 13,667 islands and total population of 259,940,857 (based on population census Dec 2010). The structure of the tectonics of Indonesia are very complex, because it is a meeting point of two tectonic plates, Indo-Australia and Eurasia, creating subduction zone and the formation of many volcanoes with about 90 of them remain active. These conditions give rise to tropical geohazards as well as earthquakes, volcanic eruptions, landslides, floods and forest fires. Some of them recorded as staggering world disasters such as Tambora volcanic eruption in 1815 and Krakatau eruption in 1883. In addition, in December 2004 a devasting Tsunami struck Aceh Province. Based on the Asia Pacific Disaster Report prepared by the UN International Strategy for Disaster Reduction (UN/ISDR) and the UN Economic Commission for Asia and the Pacific (ESCAP) on 26 October 2010, during 1980-2009 period in Asia Pacific, Indonesia has fourth ranked in the list of highest natural disasters about 312 cases, second ranked in the list of highest number of death approximately 191.164 people also has caused economic losses of at least US 22.5 billion. In this paper we can learn on disaster management in Indonesia with case studies in Jakarta and Yogyakarta Provinces.

关键词： Disasters

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GLCM Feature Extraction and PCA for Tuberculosis Detection with Neural Network

GLCM Feature Extraction and PCA for Tuberculosis Detection w...

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2022 International Seminar on Application for Technology of Information and Communication, iSemantic 2022

作者： Alfa Farah, M. Nafis Hayyin Suristiyanti, Wiwiek Ibad, Sholihul Pramunendar, Ricardus Anggi Fajar Shidik, Guruh Dian Nuswantoro University Faculty of Computer Science Postgraduate Program in Informatics Engineering Indonesia Dian Nuswantoro University Faculty of Computer Science College Teacher in Informatics Engineering Indonesia

ISBN: (数字)9781665488396

ISBN: (纸本)9781665488396

Automatic recognition system for medical images is quite a challenging job in the medical image processing field. X-rays, CT, and MRI all provide medical pictures and other modalities which are utilized for diagnostic purposes. As in medical sector, detecting tuberculosis (TB) is a very important stage before further treatment is carried out. Human interpretation of a vast array of X-ray pictures can result in detection mistakes, so an automatic recognition system is needed that can detect TB disease. In this study, we use a dataset with two classes and extract GLCM-based texture features from each class, and apply them to a two-layer feed-forward neural network, which gives a classification rate of 99%. © 2022 IEEE.

关键词： Diagnosis

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A Machine Learning Pipeline for Emotion Recognition based on Brain Topographic Maps Derived from Electroencephalogram Signals 37

A Machine Learning Pipeline for Emotion Recognition based on...

引用

37th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2024

作者： Alves, Bruno Cascaes Melo, Marla Pereira Cerri, Artur Melchiori de Freitas, Larissa Astrogildo Adamatti, Diana Francisca de Aguiar, Marilton Sanchotene Postgraduate Program in Computing Federal University of Pelotas Pelotas Brazil Undergraduate in Computer Science Federal University of Pelotas Pelotas Brazil Postgraduate Program in Computing Federal University of Rio Grande Rio Grande Brazil

Emotion recognition is an increasingly relevant field due to its direct implications for various sectors of society. The area aims to enhance the understanding of how emotions influence human behavior. Exploring brain activity analysis through electroencephalogram signals becomes possible when considering that emotions can manifest non-verbally. In this scenario, machine learning applications prove promising due to the complexity of recognizing emotions from electrical signal data from the brain. The case study focuses on DEAP, a recognized dataset constructed through experiments in electroencephalography, exposing subjects to musical and visual stimuli. The main objective of this work is to present a pipeline for the classification of emotions based on images of topographic maps generated from the EEGLAB tool and electroencephalogram signals. Additionally, the contributions of this work include the presentation of a structured dataset created through the mapping of temporal, spatial, and frequency data derived from topographic images and models for predicting dimensional emotions of arousal and valence based on the new dataset. Results demonstrate accuracies of 85.46% and 85.05% for the classification of low/high arousal and valence emotions, respectively. Copyright © 2024 by the authors.

关键词： Emotion Recognition

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Benefits and Threats of Telemedical Application in Psychiatric Services 1

Benefits and Threats of Telemedical Application in Psychiatr...

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1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Martaningga, Farra Mantoro, Teddy Andoko, Djoko Postgraduate Program of Medical Intelligence National Intelligence College Bogor Indonesia Sampoerna University Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350360554

Health development is one part of national development. Telemedical is an innovation in engineering and computing application technology healthcare in the era of society 5.0 is needed as a supporting tool. The purpose of this paper is to explain the benefits and threats of using telemedicine in the field of psychiatry in the care system. This study uses a qualitative descriptive method, data collection by literature study, which is a method that explains a phenomenon regarding the benefits and threats of telemedicine in psychiatric services. Telepsychiatry is a health service carried out by mental medicine specialists using information and communication technology to diagnose, treat and estimate the patient's health condition in accordance with their ability and authority as evidenced by the validity of the Registration Certificate (STR) and Practice Permit (SIP) while maintaining service quality and patient safety. Telepsychiatry is carried out by mental medicine specialists with other doctors, or mental medicine specialists with patients in a Health Service Facility (Fasyankes), or between Fasyankes. As a result of the dialogue, Telepsychiatry has demonstrated significant cost-effectiveness and efficiency as a viable option to conventional psychiatric services, increasing accessibility for patients seeking providers. Innovative advances in the field of mental healthcare technology solutions have the potential to provide substantial benefits to recipients and stakeholders. Threats to telemedicine, including telepsychiatry, include misuse of patients' personal data by employees or hacking by cybercriminals for purposes that jeopardise the security of patients and the country. Special attention should be paid to the problem of misuse and hacking of patient data in telemedicine by individuals and hackers. © 2023 IEEE.

关键词： Telemedicine

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Cybersecurity Detection Using Neural Networks for Chemical Industry 1

Cybersecurity Detection Using Neural Networks for Chemical I...

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1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Pratama, Ilham Fitrah Eka Mantoro, Teddy Wijayanti, Rika Persadha, Pratama Dahlian Postgraduate Program of Medical Intelligence National Intelligence College Bogor Indonesia Sampoerna University Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350360554

Cybersecurity threats affect all sectors of the economy, especially the chemical industry. The chemical industry is a critical infrastructure vulnerable to cyberattacks. In addition to financial and reputational losses, they can also cause serious accidents (such as loss of control of hazardous materials) with serious consequences for workers, society, and the environment. Industrial control panel systems are typically embedded in a variety of physical devices. The safety of control systems is crucial for ensuring the secure functioning of industrial chemical processes. Nevertheless, the susceptibility of control systems to cyber-attacks has intensified due to the extensive deployment of actuators, sensor measurements, and wireless communications. These attacks have the potential to propagate swiftly and result in severe industrial accidents. This study was conducted as part of a systematic literature review. The purpose of this study is to analyze cybersecurity threats to the chemical industry. Research shows that although cyber attacks are highly vulnerable to the chemical industry, they can be detected through neural network-based integration (NN) without having to know the process model when large quantities of historical data are available and easy to apply. It has been shown that it can be done. It is hoped that the policy recommendations obtained from this research will provide more effective guidelines for protecting the chemical industry from the risks of cyber threats. © 2023 IEEE.

关键词： Chemical industry

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Laser Medical Technology as a Potential Weapon 1

Laser Medical Technology as a Potential Weapon

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1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Nurani, Ananda Hayyu Mantoro, Teddy Andoko, Djoko Suliantoro, Dwi Sani Postgraduate Program of Medical Intelligence National Intelligence College Bogor Indonesia Sampoerna University Departmentt of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350360554

The utilization of laser technology in medicine has transformed healthcare, providing precise and minimally invasive solutions for various medical conditions. The paper's thorough analysis of a laser weapon's damage capacity, considering spot power and size through a finite elements model (FEM), offers valuable insights for future research in related fields. Various research articles cover diverse topics such as nociceptors, skin temperature distribution, and laser-tissue interaction. Initially, the paper outlines the advantages, challenges, and best practices of laser medical technology, emphasizing the importance of integrating cutting-edge advancements. The paper introduces an innovative approach that combines burn theory and medical anatomy principles with practical tactical considerations. The paper introduces and validates a 5-layer FEM for the outer skin, employing anatomical insights and advanced equations. Through the reconstruction of temperature profiles and precise addressing of necrotic tissue distribution from a 1064 nm laser, the study determines maximum permissible human exposure as 8.93 J/cm2, 8.29 J/cm2, and 8.17 J/cm2 for spot diameters of 5 mm, 10 mm, and 15 mm, respectively. The presented findings offer crucial guidance for future military research. © 2023 IEEE.

关键词： Tissue

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