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The Scientific Progress and Prospects of Artificial Intelligence for Cancer Detection: A Bibliometric Analysis 24

The Scientific Progress and Prospects of Artificial Intellig...

引用

24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023

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

ISBN: (纸本)9798350313956

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. © 2023 IEEE.

关键词： Diseases

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Early Detection and Classification of Melanoma Based on Android MobileNet V2 Convolutional Neural Network

Early Detection and Classification of Melanoma Based on Andr...

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International Seminar on Application for Technology of Information and Communication (ISemantic)

作者： Jasmine Iswarini Dyah Prabandari Christy Atika Sari Eko Hari Rachmawanto Candra Irawan Bilal R. Altamer Mohamed Ayad Alkhafaji Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Study Program in Information Systems University of Dian Nuswantoro Semarang Indonesia Mosul University Presidency University of Mosul Mosul Iraq Department of Computer Science National University of Science and Technology DhiQar Iraq

Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer are usually done through manual screening and visual inspection. This process requires a long time, has high complexity, is subjective, and is prone to errors. CNN is one of the algorithms with advantages in accurate classification. In this research, early detection and classification of melanoma cancer were carried out based on two classes, namely benign and malignant using the Convolutional Neural Network method. Our proposed method yields an accuracy of 81.11% for the validation data. The accuracy results obtained can be improved by using more datasets and increasing the number of layers used. This study uses the CNN method using MobileNet V2 architecture to detect melanoma skin cancer. The class used is benign and malignant.

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An Investigation of Ultrashort Pulses Propagation in Atmospheric Turbulence of FSO Communications 9

An Investigation of Ultrashort Pulses Propagation in Atmosph...

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9th International Conference on Electrical Engineering, Computer Science and informatics, EECSI 2022

作者： Darusalam, Ucuk Priambodo, Purnomo Sidi Universitas Nasional Informatics Study Program Universitas Siber Asia of IEEE Photonics Society Informatics Faculty of Information and Communications Technology Jakarta Indonesia Universitas Indonesia IEEE Photonics Society Faculty Engineering Department of Electrical Engineering Depok Indonesia

ISBN: (数字)9786239213565

ISBN: (纸本)9781665470438

The atmospheric turbulence as the natural media of optical propagation for the free-space optical (FSO) communications is the great advantage to reach flexible connection and low-cost deployment but also is the major problem as well. Since, the phenomena of optical propagation in the atmosphere are random process, an optical signal is induced that produces severe effects to the performance. Thus, a method to reach best performance of FSO must be developed intensively to reduce the severe effects of atmospheric turbulence. One of the solutions to reduce those aforementioned effects is an ultrashort pulse implemented in FSO to modulate frequency carrier as the signal of optical propagation. In this paper, an investigation of an ultrashort pulse was performed through simulation. An ultrashort pulse has a great chance to be implemented in FSO since it has shorter width of pulse duration than a short pulse. An ultrashort pulse is generated using optical second harmonic pulse generator that produce a pulse at 50 fs of width. Based on the results of simulation, the ultrashort pulses showing better performance of FSO than short pulses have. © 2022 Institute of Advanced Engineering and Science (IAES).

关键词： atmospheric turbulence free-space optical communications optical propagation optical scintillation temporal broadening turbulence effects ultrashort pulses

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Optical character recognition and long short-term memory neural network approach for book classification by librarians 6

Optical character recognition and long short-term memory neu...

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6th International Conference on Mathematics, Science, and Education, ICMSE 2019

作者： Rosita, Y.D. Sukmaningtyas, Y.N. Study Program of Informatics Engineering Universitas Islam Majapahit Indonesia

The book is classified by librarians that use Decimal Dewey Classification (DDS) System. It is used for cataloging and indexing books. DDC has three divisions, a ten, a hundred, and a thousand. The book subject is reflected in each division. Commonly, to know the book content, librarians read the book title. Then, they identify the book index in DDC system. Nevertheless, it requires more time. To read the book title, Optical Character Recognition (OCR) aids them to get the book title efficiently that convert the image of the book cover into the text-editable. Librarians use a web camera to scan the book cover, especially the book title area. There are three steps for pre-processing, the lowercase changing, the useless word removing, and tokenizing. To detect the book categories, Long Short-Term Memory Neural Network is good implemented in this research. It is almost used for text classification. In this research, It gives high performance that achieves more than 92% accurately. © Published under licence by IOP Publishing Ltd.

关键词： Brain

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Design and Development of the Aceh Biodiversity Android Application 8

Design and Development of the Aceh Biodiversity Android Appl...

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8th International Conference on informatics and Computing, ICIC 2023

作者： Subianto, Muhammad Misbullah, Alim Afidh, Razief Perucha Fauzie Harnelly, Essy Irfan, Muhammad Zulfan Universitas Syiah Kuala Faculty of Mathematics and Natural Sciences Department of Statistics & Study Program of Artificial Intelligence Banda Aceh Indonesia Universitas Syiah Kuala Faculty of Mathematics and Natural Sciences Department of Informatics Banda Aceh Indonesia Universitas Syiah Kuala Faculty of Mathematics and Natural Sciences Department of Biology Banda Aceh Indonesia

ISBN: (纸本)9798350342604

Indonesia is a country with a vast archipelago and rich biodiversity, particularly in the province of Aceh. However, challenges are often encountered when exploring biodiversity due to limited information access. Providing a comprehensive source of information in this context is therefore important. This study is aimed to design and develop the Aceh Biodiversity Application, which was designed for Android-based mobile devices. In our implementation, the waterfall model is used as development method to build the application which are consisted of two core elements including the back-end REST API and the front-end Android application. The application also uses three different roles to differentiate the access, those are contributors, testers, and administrators. Finally, the functionalities testing were applied using black-box testing after the development phase. In addition, the usability testing was performed using the Post study Usability Questionnaire (PSSUQ) method. The PSSUQ results showed the efficiency of the application, with an average usability score of 5.85, signifying a high level of usability. © 2023 IEEE.

关键词： Biodiversity

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The Design of VBee Diary Writing Application 9

The Design of VBee Diary Writing Application

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9th International Conference on Education and Technology, ICET 2023

作者： Sidupa, Christiana Nugroho, Hermawan Perdani, Yella Dezas Faculty of Humanities Bina Nusantara University Digital Language Learning Center Interior Design Department Jakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Informatics Engineering Study Program Salatiga Indonesia Faculty of Humanities Bina Nusantara University Digital Language Learning Center Interior Design Department Bandung Indonesia

ISBN: (纸本)9798350358292

The development of critical thinking, creativity, and communication abilities is facilitated by the acquisition of writing skills, which are significant for students. Nevertheless, a considerable number of students presently encounter difficulties in locating the impetus and enthusiasm required for engagement in writing endeavors. The focus of the present paper is application design. The VBee application is a web-based application that facilitates the expression of user creativity and fosters a deeper appreciation for the art of writing. The application boasts a highly intuitive interface that effortlessly enables users to document their thoughts and experiences. It offers a plethora of features that not only facilitate writing but also foster self-expression, including customizable emoticons and the option to provide feedback. By designing the application, it could help support vocational school students in improving the quality of skill-focused education, particularly their English creative writing skill in enjoyment. Besides, the teachers are assisted to guide their students with technologically advanced and entertaining learning tools. © 2023 IEEE.

关键词： Students

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Villages Status Classification Analysis Involving K-Means Algorithm to Support Kementerian Desa Pembangunan Daerah Tertinggal dan Transmigrasi Work programs 1

Villages Status Classification Analysis Involving K-Means Al...

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1st International Conference on Advanced Information Scientific Development, ICAISD 2020

作者： Hasugian, Paska Marto Hutahaean, Harvei Desmon Sinaga, Bosker Sriadhi Silaban, Saranom Informatics Engineering Study Program STMIK Pelita Nusantara Computer Science and Informatics Education Study Program Faculty of Engineering Universitas Negeri Medan Medan20221 Indonesia

Data mining is a technique of extracting information that has not been known before in a collection of data in the database. Data mining has been applied in various fields that require extracting information, some of the work that can be generated with data mining is classification, prediction, and data grouping. In this study, an analysis of village data collection was carried out to explore the potential or knowledge of the data that has been presented with the main objective of producing a grouping of village status. To support clustering or grouping activities the K-means algorithm used with the general process is to carry out the modeling process without supervision and is one of the methods for grouping data with a system partition, with the principle of allocating each data to the centroid or the closest average, work steps conducted in support of this research is to collect data related to the analysis of data grouping and proceed with the calculation process in accordance with the work steps of the K-means algorithm, the amount of data used as a test of 303 villages scattered in the old Padang regency. The results of calculations by displaying a new group of Cluster 0 is occupied by 120 villages, cluster 1 with a total data of 123 villages, Cluster 2 with a total of 6 villages, cluster 3 with a total of 33 villages while cluster 4 with a total of 21. © 2020 Published under licence by IOP Publishing Ltd.

关键词： K-means clustering

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Trajectory Analysis of Inter-Island Logistics Transportation for Aggregate Material Using Web-Based Information 2

Trajectory Analysis of Inter-Island Logistics Transportation...

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2nd International Conference on Technology Innovation and Its Applications, ICTIIA 2024

作者： Suraji, Aji Ishak, Syarifuddin Prabowo, Prabowo Fatkhurrozi, Muhammad Alawy, Gholiqul Amrodh Putra, Rangga Pahlevi University of Widyagama Malang Dept. of Civil Engineering Malang City Indonesia Malang State University Study Program of D4 Eng. Tech and Civil Building Maintenance Malang City Indonesia Institut Teknologi Sumatera Dept. of Ocean Engineering Lampung Selatan Regency Indonesia University of Widyagama Malang Dept. of Informatics Engineering Malang City Indonesia

ISBN: (纸本)9798350351613

Transportation of material aggregates over long distances and between islands requires a long time by changing modes of transportation. Therefore, determining a material aggregate travel trajectory model using a web database is something that can help in logistics movement analysis. This study aims to create a web-based material aggregate transportation trajectory model. The data collection method involves extracting data with Google Maps which shows distance and time indications. Next, validation is carried out in the field with a direct survey at the location. The analytical method uses statistical methods to create modeling using a linear regression model approach and statistical tests using anova. The results of the study show that the linear regression model is simple with an independent variable coefficient of 0.0306 and an R-square of 0.8649. Meanwhile, using the ANOVA test, it was stated that the modeling results were quite significant and the model could be used to make predictions. © 2024 IEEE.

关键词： aggregate material logistics trajectory transportation web-based information

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Design Enterprise Architecture Using the TOGAFADM Framework to Support Academic Information Systems at Nusa Nipa University

Design Enterprise Architecture Using the TOGAFADM Framework ...

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Smart Technology (ICE-SMARTec), IEEE International Conference on

作者： Yohanes Brekmans M. Darkel Andi W. R. Emanuel Paulus Mudjihartono Faculty of Engineering Informatics Engineering Study Program Universitas Nusa Nipa Indonesia Departemen Informatika Fakultas Teknologi Industri Universitas Atma Jaya Yogyakarta Yogyakarta Indonesia

Information technology support is desperately needed for higher education. Universities must use information technology to effectively and efficiently manage potential resources to compete with other institutions. Utilization of IT in Higher Education Governance, particularly the academic information system at Nusa Nipa University, lacks a structured architecture. The current IT infrastructure is insufficient to respond promptly and precisely to application and business change solutions. This study aims to simplify the process of developing information system architecture by developing an architectural model and an implementation roadmap. This study's design uses the TOGAF ADM model, The organization's initial condition analysis stage is the preliminary requirement management phase; architectural vision; and business architecture. The enterprise architecture design begins with the second stage's information system architecture and technology architecture phases. The subsequent phases of opportunities and solutions, migration planning, and change management, recommendations for implementing enterprise architecture are presented in the third section. The consequences of this study are IT outlines for each engineering stage given the TOGAF ADM structure for business processes in new understudy affirmations frameworks, scholastic cycles, graduated classes, and libraries to help data frameworks at Nusa Nipa College. This research can create a blueprint for IT development suggestions for expected business techniques at Nusa Nipa College.

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AlexNet Architecture Based Convolution Neural Network for Realtime Audio to Text Translator of Bisindo Hand Sign

AlexNet Architecture Based Convolution Neural Network for Re...

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International Seminar on Application for Technology of Information and Communication (ISemantic)

作者： Dhiki Sujatmiko Christy Atika Sari Eko Hari Rachmawanto Andi Danang Krismawan Bilal R. Altamer Mohamed Ayad Alkhafaji Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Study Program in Animation University of Dian Nuswantoro Semarang Indonesia Department of Computer Science Mosul University Presidency University of Mosul Mosul Iraq Department of Computer Science National University of Science and Technology DhiQar Iraq

Deafness is a condition that results in the loss of hearing function, hindering the reception of information such as oral communication that relies on auditory senses. Consequently, individuals with hearing impairment experience communication barriers and may have limited or no ability to respond. One solution is the use of sign language. In Indonesia, there are two known sign languages: Sibi and Bisindo. Both serve the same function but differ in their style of movement and expression. Bisindo is considered more flexible as it conveys meaning based on the Indonesian language. However, the universal understanding of this language solution is still limited among many people. Therefore, a program is needed to facilitate translation between deaf individuals who use sign language and their counterparts who do not communicate through sign language. CNN (Convolutional Neural Network) is a deep learning algorithm used for training visual input data recognition by computer systems. There are various CNN-based architectures, and one of them is AlexNet. Based on the author's testing, the AlexNet architecture proves to be suitable for real-time sign language translation. The evaluation of the system involved 7,800 datasets and 520 testing instances, with an average accuracy of 468 correct translations. When averaged, the system achieved a 90% accuracy rate, representing a 100% increase in accuracy compared to previous approaches.

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