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Information Technology and Computing (ICITCOM), International Conference on

作者： Debby Alita Imam Ahmad Rhaishudin Jafar Rumandan Moh Erkamim Widyasmoro Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Islamic Education Management Study Program Institut Agama Islam Negeri Ambon Ambon Indonesia Smart City Information Systems Study Program Universitas Tunas Pembangunan Surakarta Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350379839

ISBN: (纸本)9798350379846

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data.

关键词： Pediatrics Accuracy Computational modeling Prevention and mitigation Data models Classification algorithms Decision trees Data mining Information technology Diseases

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A Comparison of Multi Class Support Vector Machine vs Deep Convolutional Neural Network for Brain Tumor Classification

A Comparison of Multi Class Support Vector Machine vs Deep C...

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

作者： Nur Ryan Dwi Cahyo Christy Atika Sari Eko Hari Rachmawanto Cahaya Jatmoko Rabei Raad Ali Al-Jawry Mohamed Ayad Alkhafaji Department of Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Department Computer Science Northern Technical University Semarang Indonesia Department of Computer Engineering Technology Northern Technical University Mosul Iraq Department of Computer Sciece National University of Science and Technology DhiQar Iraq

Multi SVM has long been one of the popular methods in classification, while DCNN has recently gained significant attention in image processing and pattern recognition. This research evaluates the effectiveness of Multi Class Support Vector Machine (M-SVM) and Deep Convolutional Neural Network (DCNN) techniques in classifying brain tumors. A dataset of 2660 3D medical images with dimensions 227 x 227 x 3; including Glioma, Meningioma, and Pituitary tumors, has been partitioned into distinct sets for both training and testing purposes. DCNN approach achieves excellent accuracy in identifying tumor names, with a training accuracy of 97.8% and 100% success rate in 9 experiments. The Multi SVM method demonstrates relatively good accuracy, with training accuracies ranging from 70% to 90% based on different kernel functions. These findings provide valuable insights for selecting appropriate methods in brain tumor classification and encourage further exploration of hybrid Multi SVM-DCNN approaches to enhance accuracy and reliability.

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Development Model for Knowledge Management System (KMS) to Improve University's Performance (Case Studies in Indonesia University of Education)

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International Journal of computer science Issues 2012年第1 1-1期9卷 1-6页

作者： Munir Rohendi, Dedi Study Program of Computer Science Faculty of Mathematics and Sciences Education Indonesia University of Education Bandung Indonesia Mechanical Engineering Education Department Faculty of Technology and Vocational Education Indonesia University of Education Bandung Indonesia

Knowledge Management System (KMS) is one way to organize and documented the knowledge of institution. The purpose of this study is to develop a prototype KMS in organizing and documenting the knowledge in the university and to do a document aggregation based on the total number, subjects and writers (lecturers). The development method of KMS prototype is using sharepoints which are able to collect, store and publish all digital data available at the university which can be accessed online. Aggregation is using the percentage between the number of documents, subjects, and writers (lecturers). The aggregation's result between the number of digital files compared to the number of courses and the number of lecturers are each below 10%. In the future, the university still needs to encourage all lecturers or academic community to increase the collection of digital files that can indirectly improve the quality and educational services. © 2012 International Journal of computer science Issues.

关键词： Knowledge based systems

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Twitter Data Sentiment Analysis of COVID-19 Vaccination using Machine Learning

Twitter Data Sentiment Analysis of COVID-19 Vaccination usin...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Fairuz Iqbal Maulana Puput Dani Prasetyo Adi Dian Lestari Agung Purnomo Sukeipah Yuli Prihatin Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia National Research and Innovation Agency Telecommunication Research Center Jakarta Indonesia Faculty of Medicine Airlangga University Surabaya Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Informatics Study Program Politeknik Kota Malang Malang Indonesia

The expansion of the web is accelerating, which helps encourage the creation of fresh ideas. In today's internet era, we must suggest techniques to filter out various information. Social media sentiment analysis based on Twitter data can monitor the real-time monitoring of the COVID-19 vaccine. In this way, relevant organizations or governments can take proactive steps to address misinformation and inappropriate behaviour around the COVID-19 vaccine, which threatens the success of the national vaccination campaign. The purpose of this research is to determine if there is a link between how people feel about the COVID-19 vaccine on Twitter and how many people actually get vaccinated against it. This study uses the COVID-19 All Vaccines Tweet dataset sourced from Kaggle. This research Identifies public sentiment, emotion, word usage, and trend of all filtered tweets. The results show that there are 31% positive tweets, 10% negative tweets, and 58% neutral tweets. Tweets with neutral subjective valence tend to cluster in the middle of the polarity scale (between -1 and +1), whereas tweets with strong subjective valence are spread across the scale.

关键词： COVID-19 Seminars Sentiment analysis Social networking (online) Blogs Tag clouds Real-time systems

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Application of Message Security Application Using Vigenere Cipher Algorithm Utilizing One Time Pad (OTP) Algorithm as a Key Generator 1

Application of Message Security Application Using Vigenere C...

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1st Workshop on Environmental science, Society, and Technology, WESTECH 2018

作者： Pardede, A.M.H. Br Sitepu, Lorena Perbina Zarlis, Muhammad Tulus Iskandar, Akbar Sriadhi, S. Manurung, Rosida Tiurma Siregar, Nurintan Asyiah Sari, Ayu Esteka Yunawati, Sri Mursyidah, M. Mursalin, M. Kurniasih, Nuning Kurniawan, Citra Winarno, Edy STMIK Kaputama Sumatera Utara Binjai Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Program Study of Accounting Pasir Pengaraian University Riau Indonesia Departement of Information Technology and Computer Politeknik Negeri Lhokseumawe Aceh Indonesia Department of Mathematics Education Universitas Malikussaleh Aceh Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Electrical Engineering Sekolah Tinggi Teknik Malang Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia

Cryptography is the science and art of maintaining the security of messages when messages are sent from one place to another. One of the ways securing the form of text message information is by the encryption process using the Vigenere Cipher algorithm and utilizing the One Time Pad (OTP) algorithm as a key generator, where the message will be random when it is opened. The message encryption process used the vigenere cipher algorithm while OTP is used to secure the key with the same formula. After this research has been done, an application was designed to secure text messages by converting the text message into a random message so that the message was unreadable due to a secret message that could not be known by others. The results achieved can secure an encrypted message that cannot be reopened and if those messages were reopened, they must be decrypted. © Published under licence by IOP Publishing Ltd.

关键词： Cryptography

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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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On the Okamoto-Uchiyama cryptosystem: (A brief essay on basic mathematics applied in cryptography)

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Journal of Physics: Conference Series 2019年第4期1341卷

作者： Loeky Haryanto Armin Lawi Suhastina Suhastina Putri Qarynah Corresponding author Lecturer at Computer Science Study Program Students at Computer Science Study Program Mathematics Department Hasanuddin University Makassar Indonesia

The Okamoto-Uchiyama cryptosystem applies many consepts of basic abstract algebra, discrete mathematics and number theory. Many of these concepts are elementary and used in other branches of cryptography. However, those elementary concepts are not enough provided in the mathematics curriculla in under developed and developing countries despite the fact that in early stages teaching of those basic mathematics concepts, there is no need to provide sophiticated nor rigorous treatments beyond computations of integers. By exploring the basic mathematics applied in Okamoto-Uchiyama's algorithm and its re-lated concepts, this exploration should make mathematics teachers, educators and instructors to be aware of the important teaching the basic abstract algebra, discrete mathematics and number theory as early as high school senior level or at the first year in colleges and universities.

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Perception analysis of the Indonesian society on twitter social media on the increase in BPJS kesehatan contribution in the Covid 19 pandemic era 10

Perception analysis of the Indonesian society on twitter soc...

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10th International Conference and Workshop on High Dimensional Data Analysis, ICW-HDDA 2020

作者： Permana, F.C. Wicaksono, Z.M. Kurniawan, C. Abdullah, A.S. Ruchjana, B.N. Study Program of Multimedia Education Universitas Pendidikan Indonesia Jl. Dr. Setiabudi No.229 Bandung40154 Indonesia Student of Master of Management Program Universitas Padjadjaran Jl. Raya Bandung Sumedang km 21 Jatinangor Sumedang45363 Indonesia Department of Computer Science Universitas Padjadjaran Jl. Raya Bandung Sumedang km 21 Jatinangor Sumedang45363 Indonesia Department of Mathematics Universitas Padjadjaran Jl. Raya Bandung Sumedang km 21 Jatinangor Sumedang45363 Indonesia

In the conditions of the Covid-19 Pandemic, the president of Indonesia, Ir Joko Widodo, on May 13, 2020, announced an increase in BPJS Kesehatan contribution. This announcement made everyone in the community boisterous, including Indonesians on social media twitter. Currently, Indonesia is ranked fifth in the world using social media twitter, so data mining on Twitter is a good opportunity to see the public's response to a developing issue. This paper will discuss perceptions analysis of the Indonesian people on social media regarding the issue of increasing the contribution of BPJS Kesehatan. The issue of increasing the contribution of BPJS Kesehatan has been a topic of conversation on Twitter for a long time. After 30 days of data crawling, 145,359 tweets were obtained. This amount of data proves that the Indonesian people are very active in issuing opinions regarding the issue of increasing contribution BPJS Kesehatan. Various kinds of differences of opinion in each conversation are classified into three types of opinion using the Naive Bayes method. The three types of opinions are classified into positive opinions, negative opinions, and neutral opinions. The opinion classification results obtained were 73% containing negative opinions, 18% positive opinions, and 9% neutral opinions. This can serve as an early warning for the government to see the public's response in every policy taken. So that each policy can be evaluated for the better. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Data mining

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Retracted: Sylabus and Matrials Design for Vocational Student and Its Dissemination Using Website

Retracted: Sylabus and Matrials Design for Vocational Studen...

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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： Harahap, Astro Julida Ongko, Erianto Manurung, Hotler Kurnia, Dian Hartono, H. Abdullah, Dahlan Erliana, Cut Ita Djanggih, Hardianto Saddhono, Kundharu Rianita, Dian Setiawan, Muhammad Ikhsan Setiawan, Yuliyanto Budi Manurung, Rosida Tiurma Sriadhi, S. Sinurat, Mangasi Siregar, Aisyah Soni Hutauruk, Rapat Piter Sibarani, Nico Benjamain Department of Informatics Akademi Teknologi Industri Immanuel Medan Indonesia Department of Computer Systems Universitas Pancabudi Medan Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Law Universitas Tompotika Luwuk Banggai Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Administration University of Lancang Kuning Pekanbaru Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia Study Program of Communication Studies Universitas Semarang Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia STIE Bina Karya Tebing Tinggi Indonesia

The learners' needs are an important factor in designing syllabus and materials design, this research deals with the syllabus and material design based on the professional's needs. It is expected that the syllabus and materials designes are communicatively applicable to the professional academy. Descriptive method is applied in this research. The sample of this research is 30 students of ATII Immanuel Academy Medan. They were selected by random sampling to get the data, the questioners were administered to students. the questioners consisted of 54 items and the semi structured interview consisted of 5 questions, the finding indicated that learners' needs were focused on reading and speaking skills. With reference appropriately and proportionally derived for students of the Professional Academy. Further on the basis of the syllabus, materials are designed in which the skills of using language become a priority. The results of this research will be disseminated using the website. © Published under licence by IOP Publishing Ltd.

关键词： Information systems

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The Impact of Language Expressions and Visual Exploration on Neurodivergent Artist Quotes in Educational Setting

The Impact of Language Expressions and Visual Exploration on...

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International Conference on Business and Industrial Research (ICBIR)

作者： Desi Indrawati Yuda Suryasa Sjaerodji Aris Darisman Imaniar Rizki Waridha Computer Science Department Language Center Faculty of Humanities Bina Nusantara University Bandung West Java Indonesia Visual Communication Design Study Program School of Design Bina Nusantara University Bandung West Java Indonesia

ISBN: (数字)9798350383027

ISBN: (纸本)9798350383034

In recent years, neurodiversity has gained popularity among those proponents of people's inclusion, dignity, and rights. Demonstrations and images help them learn more effectively. Give written instructions, visual clues, and brief spoken instructions when feasible. Furthermore, the researchers included seventeen student populations, eleven officers and staff, and twelve lecturer populations. For two days in a row, they attended the interactive quotation display by neurodivergent artists, and in response, they contributed drawings that reflected their interpretations of the quotes. An interview served as the second method of gathering data. The researchers also conducted a structured interview with four students, four officers, and three lecturers acting as spokespeople. Quotes from the works of Neurodivergent Artists such as Nintendo, Love, Amsterdam, Suzanne, Kacamata (Glasses), Teman (Friends), Mudik (Homecoming), Menjahit (Sewing), and Iggle can be found in the Interactive Installation activity. Using a mixed-methods approach, the researchers collected and examined the data (Creswell, 2014). It is an approach that blends qualitative and quantitative research techniques. According to the findings, the Amsterdam quote is liked by lecturers, staff, and students alike. In addition, the Love quote sparks curiosity in both students and instructors, indicating a mutual admiration for its meaning.

关键词： Visualization Glass Semiotics Sparks Interviews Business

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