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

作者： Edy Prayitno Rikie Kartadie Uning Lestari Munengsih Sari Bunga Accounting Information Systems Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Computer Engineering Study Program Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Informatics Study Program Faculty of Science and Information Technology Universitas Akprind Indonesia Yogyakarta Indonesia Department of Computer Engineering Smart City Information Systems Politeknik Negeri Indramayu Indramayu Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

The increasing use of digital payment systems has led to a rise in fraudulent activities, presenting a significant challenge in ensuring secure transactions. This research focuses on implementing the Support Vector Machine (SVM) algorithm with a Radial Basis Function (RBF) kernel to detect fraud in digital payment systems. One of the main challenges addressed in this study is the severe class imbalance in the dataset, where fraudulent transactions account for only 0.17% of total transactions. To overcome this, the SMOTE (Synthetic Minority Over-sampling Technique) method was applied to balance the dataset, allowing the model to better recognize fraudulent patterns. The results indicate that the SVM model achieved an accuracy of 99.93%, with a precision of 86.23% and a recall of 75.51%. These results demonstrate that SVM, combined with SMOTE and RBF kernel, is highly effective in detecting fraudulent transactions while minimizing false positives. This research provides a strong foundation for improving fraud detection models in the context of digital payment systems, offering enhanced security and trust for users. Further research could explore hybrid models and real-time data analysis to improve performance.

关键词： Support vector machines Seminars Adaptation models Accuracy Data models Real-time systems Fraud Security Kernel Intelligent systems

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HFLTS-TOPSIS with Pseudo-distance in Determining the Best Lecturers 1

HFLTS-TOPSIS with Pseudo-distance in Determining the Best Le...

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

作者： Abdullah, Dahlan Hartono, H. Saddhono, Kundharu Kurniasih, Nuning Iskandar, Akbar Rianita, Dian Purwarno Setyawasih, Rianti Satria, Erwinsyah Nuryanto, Tato Herawati, Lilik Sujinah Sudarsana, I Ketut Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Department of Public Administrations Universitas Lancang Kuning Indonesia Faculty of Literature Universitas Islam Sumatera Utara Medan Indonesia Indonesia Department of Management Faculty of Economic Universitas Islam 45 Bekasi Indonesia Faculty of Teacher Training and Education Universitas Bung Hatta Padang Indonesia FITK IAIN Syekh Nurjati Cirebon Indonesia Department of Indonesian Language Teaching Institut Agama Islam Negeri Syekh Nurjati Cirebon Cirebon Indonesia Faculty of Education University Muhammadiyah of Surabaya Surabaya Indonesia Department of Religious Education Institut Hindu Dharma Negeri Denpasar Indonesia

Decision making is sometimes faced with a situation where assessment is given in the form of linguistic variables, which have a certain range of values so that decision making cannot be given in the form of numerical values. One approach commonly used is Hesitant Fuzzy Linguistic Term Sets (HFLTS) which is a multi-criteria and multi-alternative decision making method. In TOPSIS which has the concept of distance measurement, basically the chosen one is the best alternative is an alternative that has the closest distance to a positive solution and the farthest distance with a negative solution. The incorporation of HFLTS-TOPSIS has the advantage that decision making can be done in the form of variable linguistics and also a situation where there are benefit criteria and cost criteria. This study will use the HFLTS-TOPSIS approach that has been modified in the distance calculation section so that distance calculation is based on the difference of preference degree between the two HFLTS. The results of research conducted by a number of researchers show that using pseudo-distance will provide advantages compared to the standard HLFTS-TOPSIS. Pseudo-distance HFLTS-TOPSIS will be applied in the selection of the best lecturers. The criteria used in this study are: Student Satisfaction, Research, Number of late, and number of complaints from students. © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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Greybody factor for massive fermion emitted by a black hole in de Rham-Gabadadze-Tolley massive gravity theory

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Physical Review D 2021年第8期104卷 084054-084054页

作者： P. Boonserm C. H. Chen T. Ngampitipan P. Wongjun Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok 10330 Thailand Thailand Center of Excellence in Physics Ministry of Higher Education Science Research and Innovation Bangkok 10400 Thailand The institute for fundamental study Naresuan University Phitsanulok 65000 Thailand Physics Program Faculty of Science Chandrakasem Rajabhat University Bangkok 10900 Thailand

The greybody factor of the massive Dirac field around the black hole in the dRGT massive gravity theory is investigated using the rigorous bound and the WKB approximation methods. In both methods, the greybody factor significantly depends on the shape of the potential. If the potential is smaller, there is more probability for the Dirac field to transmit through the black hole, therefore, the greybody factor is higher. Moreover, there exists a critical mass of the Dirac field such that the greybody factor is maximum. By comparing the results from these two methods, we argue that it is useful to use the rigorous bound method for the low potential cases, while using the WKB approximation method for the high potential cases.

关键词： Alternative gravity theories Classical black holes Quantum aspects of black holes

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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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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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Stunting Classification in Toddlers: Implementation and Evaluation of the Decision Tree Algorithm

Stunting Classification in Toddlers: Implementation and Eval...

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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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Young Lunar Crescent Detection Based on Video Data with computer Vision Techniques

SSRN

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SSRN 2022年

作者： Utama, Judhistira Aria Zuhudi, Alif Rizza Prasetyo, Yudi Rachman, Abdul Riadi, A.R. Sugeng Nandi, Cep Riza, Lala Septem Department of Physics Education Universitas Pendidikan Indonesia Bandung Indonesia Department of Computer Science Education Universitas Pendidikan Indonesia Bandung Indonesia Pusat Riset Antariksa Badan Riset dan Inovasi Nasional Timau Indonesia As Salaam Observatory Surakarta Indonesia Study Program of Geography Education Universitas Pendidikan Indonesia Indonesia

More than one and a half billion people worldwide use a calendar based on the young lunar crescent apparition. In the Hijri calendar, it is crucial to recognize the appearance of the lunar crescent for the first time after conjunction, especially for the three critical months of Ramadan, Shawwal, and Dzulhijjah. Using computer vision algorithms, this work uses video data to identify the young lunar crescent’s appearance. The lunar crescent will be captured using Gaussian Blur and Adaptive Thresholding. Image processing techniques, such as frame extraction from video, pre-processing images, and detection algorithms that may detect the lunar crescent utilizing Circular Hough Transform (CHT), are all are implemented using the OpenCV package. We chose ten observations as a sample provided by the Meteorological, Climatological, and Geophysical Agency (MCGA). The computation time of the proposed model is relatively faster than the frequency of the frames displayed per second on the video. This program's accuracy in distinguishing among frames with and without the lunar crescent is quite good. We conclude that the proposed model can accurately and quickly detect when the young lunar crescent will appear. © 2022, The Authors. All rights reserved.

关键词： computer vision

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Adjusted Framework of M-Learning in Blended Learning System for Mathematics study Field of Junior High School Level VII

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IOP Conference Series: Materials science and Engineering 2018年第1期336卷

作者： Lipur Sugiyanta Moch. Sukardjo Study Program of Education for Informatics and Computer Engineering/Faculty of Engineering State University of Jakarta

The 2013 curriculum requires teachers to be more productive, creative, and innovative in encouraging students to be more independent by strengthening attitudes, skills and knowledge. Teachers are given the options to create lesson plan according to the environment and conditions of their students. At the junior level, Core Competence (KI) and Basic Competence (KD) have been completely designed. In addition, there had already guidebooks, both for teacher manuals (Master's Books) and for learners (Student Books). The lesson plan and guidebooks which already exist are intended only for learning in the classroom/in-school. Many alternative classrooms and alternatives learning models opened up using educational technology. The advance of educational technology opened opportunity for combination of class interaction using mobile learning applications. Mobile learning has rapidly evolved in education for the last ten years and many initiatives have been conducted worldwide. However, few of these efforts have produced any lasting outcomes. It is evident that mobile education applications are complex and hence, will not become sustainable. Long-term sustainability remains a risk. Long-term sustainability usually was resulted from continuous adaptation to changing conditions [4]. Frameworks are therefore required to avoid sustainability pitfalls. The implementation should start from simple environment then gradually become complex through adaptation steps. Therefore, our paper developed the framework of mobile learning (m-learning) adaptation for grade 7th (junior high school). The environment setup was blended mobile learning (not full mobile learning) and emphasize on Algebra. The research is done by R&D method (research and development). Results of the framework includes requirements and adaptation steps. The adjusted m-learning framework is designed to be a guidance for teachers to adopt m-learning to support blended learning environments. During mock-up prototype, the ad

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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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Blockchain Technology Based Credibility Verification in E-Journal Entities

Blockchain Technology Based Credibility Verification in E-Jo...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Watini, Sri Kedah, Zulkarnain Lukita, Chandra Sokibi, Petrus Mustika, Gadis Rahardja, Reymund Yulianjani, Arsi Sukmana, Husni Teja University of Panca Sakti Bekasi Early Childhood Teacher Education Bekasi Indonesia University of Malaysian Computer Science Vice Chancellor Selangor Malaysia University of Catur Insan Cendekia Information System Cirebon Indonesia University of Raharja Information System Tangerang Indonesia University of Raharja Digital Business Tangerang Indonesia University of Raharja Information Management Study Program Tangerang Indonesia Syarif Hidayatullah Islamic University Lecture of Information Engineering Jakarta Indonesia

ISBN: (纸本)9781665468763

In the industrial era 4.0, it has surpassed increasingly complex technological advances in the information system that required a very high infrastructure and facilities and prevented fraud. Counterfeiting is a procedure following an entity, statistics, or documents (observe forged documents) with plans to deceive. Falsification of extensive information certificates is exacerbated by the current economic situation in Indonesia, which is currently occurring due to the widespread epidemic, namely COVID-19. The spread of the COVID-19 outbreak has had a significant impact and changes in all sectors, especially certificate forgery in Indonesia. The imitation of busy certificates is the main focus of this journal, focusing on journal publications combined with Blockchain technology. The sophistication of blockchain technology as authentication is comparing two or more items or additional tests to ensure the accuracy, correctness, or correctness of the information. This method uses qualitative methods with data sources based on case studies in controlled supervision with the basic concept of cryptography as the basis of analysis. From the decisions made, it is hoped that this will minimize the level of forgery of certificates widely measured during the COVID-19 era. © 2022 IEEE.

关键词： Blockchain

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