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International Conference on Computing, engineering, and Design (ICCED)

作者： Rahmat Hidayat Achmad Solichin Adhitia Erfina Sudin Saepudin Muhamad Muslih Mohd Zainuri Saringat Master of Computer Science Budi Luhur University Jakarta Indonesia Information Systems Study Program Nusa Putra University Sukabumi Indonesia Department of Software Engineering Faculty of Computer Science and Information Technology Tun Hussein Onn Malaysia University

ISBN: (数字)9798331529376

ISBN: (纸本)9798331529383

The Plasmodium parasite, which causes malaria, is an acute fever illness that infects people when a female Anopheles mosquito bites them. It is predicted that malaria would claim 619,000 lives in 2021, with 96% of those deaths occurring in the African continent. We can achieve this by using a microscope to examine thick and thin blood smears. The proficiency of a microscope examiner is crucial for doing microscopic examinations. Consider how time-consuming, ineffective, and costly it would be to examine thousands of malaria cases. Consequently, Creating an automated method for detecting malaria parasites is the aim of this study. We employ a MobileNetV2 pretrained model with CNN technology. Because it has been trained on dozens or even millions of data points, this pretrained model is incredibly light but dependable. There are two main benefits of automatic malaria parasite detection: firstly, it can offer a more accurate diagnosis, particularly in locations with limited resources; secondly, it lowers diagnostic expenses. The optimizer utilizes Adam Weight, the criteria uses NLLLoss, and the model is trained using 32 for batch_size. In the fourteenth epoch, we obtained the maximum accuracy score of 96.26% based on the training data. The outcomes of the predictions demonstrate how excellent this score is. EfficienceNet, DenseNet, AlexNet, and other pretrained models are among the alternatives that scientists are advised to try training with.

关键词： Training Adaptation models Accuracy Costs Malaria Microscopy Data visualization Training data Cost function Data models

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Exploring ERP User Behaviour in Developing Countries: Integrating Self-efficacy and UTAUT Perspectives 5

Exploring ERP User Behaviour in Developing Countries: Integr...

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5th International Conference on Advancement in Data science, E-Learning and Information Systems, ICADEIS 2023

作者： Syamsuar, Dedy Oktaharisetia, Muhammad Angga Witarsyah, Deden Luthfi, Ahmad Dell, Peter Permana, Yudistira Sira Antoni, Darius Bina Nusantara University School of Information Systems Information Systems Department Indonesia Universitas Bina Darma Program Pasca Sarjana Palembang Indonesia Telkom University School of Industrial Engineering Bandung Indonesia Islamic University of Indonesia Faculty of Industrial Technology Department of Informatics Indonesia Curtin University School of Management and Marketing Faculty of Business and Law Australia Politeknik Sekayu Teknik Informatika Sekayu Indonesia Universitas Indo Global Mandiri Faculty of Computer Science Palembang Indonesia

ISBN: (纸本)9798350303414

ERP stands for enterprise resource planning. It is an information system that is all rolled into one, is very flexible and adaptable, and optimizes business operations while also centralizing all of the company's data. This study aims to empirically investigate the elements that affect users' intention and usage of enterprise resource planning (ERP). This research incorporates self-efficacy into the unified theory of acceptance and use of technology (UTAUT2). A quantitative technique was taken, and as a result, 143 replies that might be used were effectively collected. After that, the information was put through a structural equation modelling partial least square (SEM-PLS) analysis. According to the findings of this research, self-efficacy appears to have a significant influence on all endogenous variables (EE, BI, and UB), as indicated by t-values of 3.951, 7.573, and 5.492, respectively. In addition, the analysis also indicated that PE (4.317), EE (2.397), and HM (3.084) are likewise statistically and substantively significant to BI. The result shows that the R2 for BI and UB indicate a moderate impact of 0.603 and 0.521, respectively. It is suggested that the model has valuable applications in academic and real-world contexts. © 2023 IEEE.

关键词： Enterprise resource planning

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The Scientific Progress and Prospects of Artificial Intelligence for Cancer Detection: A Bibliometric Analysis

The Scientific Progress and Prospects of Artificial Intellig...

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Fairuz Iqbal Maulana Puput Dani Prasetyo Adi Dian Lestari Sandy Vikki Ariyanto Agung Purnomo Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta Indonesia Faculty of Medicine Universitas Airlangga Surabaya Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia

Using the Scopus database, this study aims to investigate the use of artificial intelligence for cancer detection in the last ten years from 2013 to 2022. The researchers used bibliometric analysis combined with VosViewer and Rstudio software quantification method for literature analysis. The results of the flushed articles show data such as publication year, journal, country, keywords, and authors, to the highest number of citations. Common keywords used by researchers are artificial intelligence, medical, and human. Researchers limited the findings through keywords such as in the last ten years, documents are journals, and English only so that 1868 articles were obtained. The results found that Harvard Medical School affiliation had the highest number of articles, with 101 articles, by subject area, Medicine had a proportion of 41.9% (n=1320). This bibliometric study will be useful for other researchers to examine the development of research on Artificial Intelligence for Cancer Detection in the last ten years.

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Image Processing Implementation to Classify Coffee Fruit Ripeness Using K-Nearest Neighbor (KNN) Algorithm

Image Processing Implementation to Classify Coffee Fruit Rip...

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International Conference on Information Management and Technology (ICIMTech)

作者： M. Farhan Hussaini Dermawan Deden Witarsyah Dedy Syamsuar Hanif Fakhrurroja Ahmad Luthfi Muhammad Izman Herdiansyah Faculty of Industrial Engineering Telkom University Bandung Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Department of Informatics Faculty of Industrial Technology Islamic University of Indonesia Jogjakarta Indonesia Informatics Study Program Faculty of Science and Technology Universitas Bina Darma Palembang Indonesia

Coffee is one of the plantation crops that has long been a cultivated plant in Indonesia. The classification of coffee fruit maturity manually still has several weaknesses and requires a long process, has low accuracy and is inconsistent, this is because the determination is made subjectively by coffee farmers. As for the classification of coffee fruit maturity levels automatically, it can be faster with objective determination, therefore the use of image processing is relatively easier, faster, and based on a quantified descriptive assessment to determine coffee maturity. Image Processing is a method used to process or manipulate images in 2-dimensional form. In the classification process, there are many methods used to obtain classification of objects based on training data. One of the algorithms used for the classification process is K-Nearest Neighbor (KNN). KNN is a classification technique for objects based on training data that is the closest or has similar characteristics to the object. KNN includes supervised learning algorithms, where the results of the new query instance are classified based on the majority of the categories in K-Nearest Neighbors (K-NN). The finding indicated that class classification of ripe and unripe were 88,24 % and 100% respectively with 93,33% accuracy level.

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Mapping and Visualization of Artificial Intelligence for Digital Economy Research: A Bibliometric Approach

Mapping and Visualization of Artificial Intelligence for Dig...

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International Conference of computer science and Information Technology

作者： Fairuz Iqbal Maulana Agung Purnomo Andi Pramono Mohammad Nazir Arifin Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Interior Design Department School of Design Bina Nusantara University Jakarta Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia

ISBN: (纸本)9798350399080

Artificial Intelligence (AI) seems to be a disruptive technology that defines and reshapes the economy, more efficient industrial processes, new business models, and the service sector, becoming the development of different practices than before. The literature shows that it will be included in all fields and people's lives, as is the case in the digital economy. Artificial Intelligence for Digital Economy has not been studied significantly. This study uses bibliometric analysis to graphically map scientific publications and research trends in the Artificial Intelligence for Digital Economy sector around the world in the last ten years. The Scopus database was used to collect metadata information for this study, and VOSViewer was used to demonstrate bibliometric network mapping. We use an article selection procedure starting with the searched keywords and year constraints and then exporting the database to a RIS file format. Over the last ten years, we retrieved 540 scientific publications published between 2012 and 2021 from the Scopus database. From the data obtained, researchers at the Russian Federation have the most published papers indexed by Scopus among the most productive countries (N=131), the most productive authors are Petrenko, S.A. (N=4), and the most subject area is computer science (N=246). We also use VOSViewer to map the Network Theme. This study recommends incorporating research subjects Artificial Intelligence for Digital Economy: Thing, Education, Platform, Global Economy, abbreviated as TEPGE research theme.

关键词： computer science Databases Bibliometrics Taxonomy Education Metadata Market research

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Relative magnetic field and slipping effect on Casson dusty fluid of two phase fluctuating flow over inclined parallel plate

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South African Journal of Chemical engineering 2023年 44卷 135-146页

作者： khan, Dolat Kumam, Poom Kumam, Wiyada Suttiarporn, Panawan Rehman, Ali Fixed Point Research Laboratory Fixed Point Theory and Applications Research Group Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Applied Mathematics for Science and Engineering Research Unit (AMSERU) Program in Applied Statistics Department of Mathematics and Computer Science Faculty of Science and Technology Rajamangala University of Technology Thanyaburi (RMUTT) Pathum Thani 12110 Thailand Faculty of Science Energy and Environment King Mongkut's University of Technology North Bangkok Rayong Campus Rayong 21120 Thailand Special Interest Group for Modelling and Data Analytics Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus 21030 Malaysia

Due to its significant applications in magnetic devices for cell separation, magnetic drugs for cancer tumor treatment, blood flow adjustment during surgery, magnetic endoscopy, and fluid pumping in industrial and engineering processes, magnetohydrodynamics (MHD) has a wide range of applications. Therefore, the aim of this study to investigate the Relative Magnetic Field and slipping effect on Casson dusty fluid of two-phase fluctuating flow over inclined parallel plate. More exactly, the relative magnetic phenomena are fixed relatively to the plate (MFFRP) or fixed relatively to the fluid (MFFRF). The mathematical modeling was established as the set of partial differential equations for dusty Casson fluid. Buckingham's pi theorem is used to find out the dimensionless variables, to make our system dimensionless. The solution in perturb form is to find out by incorporating Poincare–Lighthill perturbation technique (PLPT). To know in-depth different parameters the graphical results for both velocities are plotted with the help of software Mathcad- 15. It is clearly detected that the relative magnetic field performs a vital part in the fluid as well as particle motion. Moreover, the relative magnetic field play a vital role in the decreasing of skin friction of both plates. © 2023

关键词： Brinkman fluid Dust particles Fluctuating vertical plate Inclined relative magnetic field PLPT

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Utilization of Linguistic Data for Learner Assessment on e-Learning: Instrument and Processing

Utilization of Linguistic Data for Learner Assessment on e-L...

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International Conference on informatics and Computing (ICIC)

作者： Wenty Dwi Yuniarti Sri Hartati Sigit Priyanta Herman Dwi Surjono Doctoral Program of Computer Science Universitas Gadjah Mada Yogyakarta Indonesia Universitas Islam Negeri Walisongo Semarang Indonesia Department of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia Department of Informatics Engineering Education Faculty of Engineering Universitas Negeri Yogyakarta Yogyakarta Indonesia

ISBN: (纸本)9798350345728

The increasingly massive use of e-Learning illustrates the speed and need for innovation in learning. According to the National Higher Education Standards (SN-Dikti), constructive alignment is required between learning outcomes, processes, and assessments to properly implement learning in e-Learning. Assessment is an essential component of e-Learning. Unfortunately, the problem of assessment in e-Learning is still found. One of them is the limitations of e-Learning in accommodating and processing various assessment data, primarily linguistic. Even though the variety of assessment data, both numerical, linguistic, and a combination of the two, supports a comprehensive assessment. On the other hand, the accommodation of linguistic data raises problems regarding how to process of unifying linguistic data is carried out. Research related to linguistic data using computing with words has been carried out, but it still needs more precise results from the unification of the linguistic data. Therefore, this study proposes providing an assessment instrument to accommodate linguistic data in e-Learning, as well as showing how to process of unifying linguistic data is carried out using 2-Tuple Fuzzy Linguistic. This approach can avoid the loss of assessment information by presenting more informative and precise results in a 2-tuple (s, α) where $s$ indicates the ability level, and α shows a comparison of abilities with other learners and the potential of the learner to achieve higher abilities. This proposal has the potential to be applied in a learner assessment system for higher education e-Learning.

关键词： Technological innovation Electronic learning Instruments Education Linguistics Proposals informatics

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Retracted: Implementation Method CUSUM to Determine the Accident Prone Areas in Web Based

Retracted: Implementation Method CUSUM to Determine the Acci...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, computer science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Dinata, Rozzi Kesuma Abdullah, Dahlan Hartono, H. Erliana, Cut Ita Riasti, Berliana Kusuma Iskandar, Akbar Sari, Ifit Novita Nurmawati, N. Nanuru, Ricardo Freedom Putri, Lusi Dwi Manurung, Rosida Tiurma Sriadhi, S. Saleh, A.A. Astari, T. Khaddafi, Muammar Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Informatics Universitas Sebelas Maret Surakarta Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Departement Of: Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia Department of Civil Engineering Universitas Lancang Kuning Pekanbaru Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Statistics Financial and Social Sciences Research Group Indonesia Department of Elementary School Teacher Education STKIP Citra Bangsa Aceh Utara Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

At the Unit Laka Lantas Polres Lhokseumawe determining accident-prone areas on roads in Lhokseumawe still using manual systems. Determination of accident-prone areas are less effective because the police Unit Laka Lantas Polres Lhokseumawe just using the data of the last year and had to repeatedly calculate manually accident-prone areas based on the number of human casualties. In this study the system implementation CUSUM method (Cummulative Summary) to determine the accident-prone areas designed using the web-based programming language PHP. In this system there are three processes to determine areas prone to accidents, the accident rate calculations based on the weighted severity, blacksite calculations using the Z-Score method for determining areas prone to accident blackspots and calculations using the CUSUM method to determine the critical points of an accident. The data used are secondary data obtained from the Police Unit Laka Lantas Polres Lhokseumawe years 2009-2013. © Published under licence by IOP Publishing Ltd.

关键词： Accidents

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Salt Hash Password Using MD5 Combination for Dictionary Attack Protection

Salt Hash Password Using MD5 Combination for Dictionary Atta...

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International Conference of computer and informatics engineering (IC2IE)

作者： Agung Nugroho Teddy Mantoro Cyber Defense Engineering Study Program Sains and Defense Technology Faculty The Republic of Indonesia Defense University Bogor Indonesia Departement of Computer Science Media-Tech Lab Sampoerna University Jakarta Indonesia

Using MD5 hashing of passwords in web logins is highly vulnerable to dictionary attacks. One online application for cracking hashed passwords using a dictionary attack that is free and easy to use is ***. Even so, the use of hashing passwords using MD5 which has a low level of security is still commonly found to secure web login passwords. This research presents an increase in security through a combination of salt hash passwords when using MD5. The methodology of this study uses a quantitative experimental method to apply hash salt passwords using the MD5 combination. The password cracking test was carried out using the *** online hash cracking application on weak passwords such as “admin” with the addition of a password hash salt using the MD5 combination. The results showed that Salt Password using the MD5 combination could not be cracked by *** using a dictionary attack.

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Challenges and Emerging Issues for Generative AI and Hyper Intelligence

Challenges and Emerging Issues for Generative AI and Hyper I...

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Cyber science and Technology Congress (CyberSciTech), IEEE

作者： Jianhua Ma Qun Jin Hui-Huang Hsu John Paul C. Vergara Antonio Guerrieri Claudio Miceli Ao Guo Faculty of Computer and Information Sciences Hosei University Japan Department of Human Informatics and Cognitive Sciences Waseda University Japan Department of Computer Science and Information Engineering Tamkang University Taiwan Department of Information Systems and Computer Science Ateneo de Manila University Philippines ICAR-CNR Italy Graduate Program in Systems Engineering and Computer Science Federal University of Rio de Janeiro Brazil Graduate School of Informatics Nagoya University Japan

ISBN: (数字)9798331532093

ISBN: (纸本)9798331532109

Generative Artificial Intelligence (GenAI) represents a significant milestone in the development of artificial intelligence, bringing sophisticated AI capabilities into daily life and work. As we approach the era of Hyper Intelligence (Hyper-I), a variety of critical challenges and emerging issues have come to light, ranging from computational complexity to ethical concerns. This paper explores the evolution of AI from the perspective of human learning, comparing machine and human intelligence, and identifying key considerations for the development of future AI systems. It also highlights the growing importance of regulating advanced AI models, such as Reinforcement Learning-based Long-Term Planning Agents, to ensure that Hyper-I remains under human control. Additionally, the paper discusses the computational complexity of transformer-based models, their applicability to intractable problems, and their role in cognitive building systems and resource-constrained environments through TinyML. By analyzing these pressing challenges, this work provides insights into the future of AI and the path toward responsible innovation in generative and hyper-intelligent systems.

关键词： Hyper-intelligent systems Ethics Technological innovation Generative AI Computational modeling Tiny machine learning Pressing Transformers Regulation Computational complexity

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