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Implementation of AI-Based Support Vector Machine Algorithm for Fraud Detection in Digital Payment Systems

Implementation of AI-Based Support Vector Machine Algorithm ...

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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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Digital Technology in Health Education Trend Mapping through Bibliometrics Analysis 4

Digital Technology in Health Education Trend Mapping through...

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4th International Conference on Informatics, Multimedia, Cyber and information System, ICIMCIS 2022

作者： Maulana, Fairuz Iqbal Lestari, Dian Widartha, Vandha Pradwiyasma Haidar, Nirwana Dirgantara, Wahyu School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Airlangga University Faculty of Medicine Surabaya60132 Indonesia Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia University of Madura Informatics Engineering Study Program Pamekasan Indonesia University of Merdeka Malang Department of Electrical Engineering Malang Indonesia

ISBN: (纸本)9781665473279

This study examines the mapping of research data on digital technology in the field of health education using bibliometric analysis method. Data was collected by identifying keywords in the Scopus database and sorting them out to sort the studies from the last 10 years (2012-2021). Through this step, a total of 1482 documents were obtained (articles, journals, proceedings, books, and others). The data is then processed using the VOSViewer instrument to obtain a visualization of the mapping analysis. This study also analyzes the network types of authors and co-authors through the VOSViewer instrument. The result of this study indicates that the most document types published within ten years are Articles (66.5%), Review (22.9%), Conference Paper (4.2%), and others. The most studied subjects are Medicine (55.7%), Nursing (9.0%), Health Professions (8.2%), Social Sciences (7.8%), engineering (3.9%), Computer Science (2.6%), Environmental Science (2.6%), Biochemistry-Genetics and Molecular Biology (2.2%), Psychology (1.6%), and Dentistry (1.3%). This study offers a written communication process and the nature and direction of developing descriptive means of counting and analyzing the various phases of communication as well as recognizing the authorship and direction of its symptoms in documents on the subject of digital technology in the health sector. © 2022 IEEE.

关键词： Mapping

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IoT: Monitoring Temperature, Water pH, and Automatic Water Drainage Systems for Gurami Cultivation

IoT: Monitoring Temperature, Water pH, and Automatic Water D...

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Networking, Electrical engineering, Computer Science, and Technology (IConNECT), International Conference on

作者： Heni Sulistiani Wijaya Saputra Dedi Darwis Auliya Rahman Isnain Ardy Rimanda Putra Yosi Khairunisa Study Program of Accounting Information System Universitas Teknokrat Indonesia Lampung Indonesia Study Program of Computer Engineering Universitas Teknokrat Indonesia Lampung Indonesia Study Program of Informatics Universitas Teknokrat Indonesia Lampung Indonesia Regional Research and Development Agency Lampung Province (Balitbangda) Lampung Indonesia

Gurami is a native fish from Indonesian waters that is much-loved by Indonesian people for daily food consumption. The gurami inhabits still waters such as swamps, lakes, and ponds. Besides that, carp cannot live in a water content that is too alkaline or acidic, the oxygen content in the water must be stable. Water quality is a very important factor and can affect the survival of cultivated fish. Several parameters must be considered in improving the development of carp, one of which is the temperature and pH of the water and automatic drainage of water. In this paper, we conduct IoT-based research that focuses on controlling water temperature and pH and automatically draining pool water. Water temperature and pH control such as a pH sensor temperature sensor and a water turbidity sensor will later be connected to the ESP 32 microcontroller which already has a wi-fi module. A system that is linked to electrical power and the internet then the sensor will read the water quality including the pH temperature value and water turbidity from inside the fish pond, after getting the data, the data will go to ESP 32. This research can help gurami cultivating farmers to make it easy to control the pH temperature and perform automatic pool water draining. The results of sensor testing with actual data are pretty accurate with the average error value of the ds18b20 sensor being 0.05% while the value of the pH sensor itself is 0.07%.

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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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Feature extraction of the Indonesian phonemes using discrete wavelet and wavelet packet transform

Feature extraction of the Indonesian phonemes using discrete...

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International Conference on information Technology and Electrical engineering (ICITEE)

作者： Risanuri Hidayat Domy Kristomo Immer Togarma Dept. of Electrical Engineering and Information Technology Gadjah Mada University Yogyakarta Indonesia Study Program of Computer Engineering STMIK AKAKOM of Yogyakarta Yogyakarta Indonesia

ISBN: (纸本)9781509041404

The development of the pattern recognition techniques in voice recognition has rapidly increased. Many methods are used to create a system that is reliable and easily accessible so that the recognition accuracy is high. To find the pattern recognition system that is robust and reliable, proper feature extraction methods are needed. In this case, the proper method of the feature extraction is an efficient and effective method when it is used in recognizing specific features of data. This paper presents an effective and efficient method of the extracting features for speech processing. The focus of this work is to explore the feature extraction methods which are the most efficient and effective in recognizing Indonesian phonemes. The Feature extraction methods used and compared in the study are the Discrete Wavelet Transform (DWT) and Wavelet Packet Transform (WPT). The wavelet transform was done on the 2 nd level until 4 th level of decomposition. The comparison of the performance of both feature extraction methods are presented at the end of this section, with a statistical comparison, to draw a conclusion that the DWT methods have a better performance in terms of effectiveness and efficiency compared with the WPT method. The results of the study show that the effectiveness ratio is 60% versus 40% and the efficiency ratio is 57% versus 43%.

关键词： Feature extraction Discrete wavelet transforms Speech recognition Euclidean distance Wavelet packets

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COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT SYSTEMS IMPLEMENTATION TO OPTIMIZE BUSINESS SUSTAINABILITY 9

COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT SYS...

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9th International Conference on information Technology: IoT and Smart City, ICIT 2021

作者： Sardjono, Wahyu Lusia, Erma Utomo, Hargo Sukardi, Samudra Rahmasari, Aninda Regent Montororing, Yuri Delano Information Systems Management Department Binus Graduate Program Bina Nusantara University Indonesia Research Capacity Building Research & Development Bina Nusantara University Indonesia Department of Management Faculty of Economic and Business Gajah Mada University Indonesia Graduate Program Faculty of Economy and Business University of Indonesia Indonesia International Relations Department Faculty of Humanities Bina Nusantara University Indonesia Industrial Engineering Study Program Bhayangkara University Indonesia

ISBN: (纸本)9781450384971

Complaint resolution that arise due to internal and external factors in a company can be monitored through the Service Recovery Index (SRI), and SRI is developed through a number of factors that influence it. Meanwhile, the SRI model needs to be developed to see the business sustainability through implementation knowledge management system in the organization. The data collection method was carried out, starting with building a research instrument based on knowledge management theory and continued with observation and distributing questionnaires to respondents who were involved in the business process of managing SRI. The data analysis method was used to process the data from the questionnaire, factor analysis method was used and the method to build the model used was the regression analysis method. The results obtained from this study are the discovery of 4 (four) factors with a number of indicators that are grouped on each formed factor, which can then be made and built a readiness model that reflects current conditions, so that it can be used to build predictions in the future related to readiness. implementation of knowledge management system development in order to support increased understanding of the service recovery index in the organization. © 2021 ACM.

关键词： Knowledge management

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Optimization of Certainty Factor Algorithm to Overcome Uncertainty in Expert System Identification of Pests and Diseases of Cocoa

Optimization of Certainty Factor Algorithm to Overcome Uncer...

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Electronic and Electrical engineering and Intelligent System (ICE3IS), International Conference on

作者： Rakhmat Dedi Gunawan Imam Ahmad Parjito Harry Anggono Ego Hengki Vernando Firman Jaya Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Information Technology Education Study Program STKIP PGRI Situbondo Indonesia

ISBN: (纸本)9781665465427

Lampung Province is one of the regions with the highest cocoa production, but many factors can interfere with cocoa production. One of them is the factor of pests and diseases of cocoa that cannot be identified and prevented beforehand. An expert system is a system that adopts expert knowledge or experts in a particular field. However, the diagnosis usually contains uncertainty in the form of answers and statements used. Certainty Factor (CF) algorithm, is one of the algorithms that is able to overcome uncertainty by providing a value for the level of trust from experts and users. However, because the CF value is based on the level of confidence in the symptoms experienced by the user, it creates a problem, namely the consistency of the user's answers. So, it is necessary to make improvements to the CF algorithm, to overcome the inconsistency of user answers through the use of Consistency Ratio (CR). Through the use of CR, inconsistencies are overcome through comparisons between the consistency index and the random index. Based on the results of the accuracy test, the proposed model is able to produce an accuracy rate of 86.67% in the diagnosis of pests and diseases on cocoa plants.

关键词： Electrical engineering Deep learning Uncertainty Production Indexes Expert systems Intelligent systems

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Collaboration model of software development

Collaboration model of software development

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International Conference on Electrical engineering and Informatics, ICEEI

作者： Tien Fabrianti Kusumasari Iping Supriana Kridanto Surendro Husni Sastramihardja Information System Program Study STMIK 1M Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Indonesia

Software development is a series of processes activity involving more than one person, especially in medium to large software projects. Each activity of software development is carried out by various combination of different individual. Collaboration occurs in every phase of the process software development. The right team collaboration method is one of the important things in success software development. This research is focused to develop collaboration model of software development to meet time schedule, budget, scope, and software quality. The collaboration model of software development is generated from survey of collaboration method (about face to face and virtual collaboration) and software development methodology especially agile methodology. The direct collaboration was used in the software specification processes, and combination (with a direct and virtual) collaboration was used during software design, implementation, and validation. Team coordination in every process of software development was done with face to face method. The same artifacts were used in this collaboration model with some collaboration software tools. Combination between face to face and virtual communication was used in this model. The model is implemented in small case software development project. During the software development, some measurement is carried out. The measurement included the measurement of project completion time, cost, software specification, and software quality. The software is developed in time schedule (two months), cost under budged, and meet specification. In addition, the software has built a fairly good quality. Thus, this collaboration model good use in software development to achieved accuracy of schedule, cost, scope, and quality.

关键词： Collaboration programming Face Software measurement Software tools Software quality

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Weed Detection Based on Fine-Tuned YOLOv5

Weed Detection Based on Fine-Tuned YOLOv5

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International Conference on information Technology and Electrical engineering (ICITEE)

作者： Indra Agustian Sunu Wibirama Igi Ardiyanto Ika Novia Anggraini Pariyanto Noviansyah Department of Electrical and Information Engineering Universitas Gadjah Mada Yogyakarta Indonesia Study Program of Electrical Engineering Universitas Bengkulu Bengkulu Indonesia Department of Electrical and Information Engineerig Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798350375817

ISBN: (纸本)9798350375824

Conventional weed control often ignores weed locations, potentially causing land damage. AI-based weed detection offers a modern solution. Unfortunately, little attention has been paid to how an augmentation technique improves performance of AI-based weed detection. To address this research gap, we proposed a weed detection model based on fine-tuned YOLOv5 to detect weeds in corn fields aged 1 to 3 weeks. YOLOv5 offers computational benefits, includes auto-augmentation capabilities, and presents a more organized visualization of the outcomes from the training data. The primary dataset used in this study comprised 3,437 images with a total of 18,267 annotated objects, including corn plants and weeds. We observed the effect of mosaic augmentation on the dataset images based on auto-augmentation in YOLOv5. We found that mosaic augmentation with a 0.75 probability outperformed 0.5 and 1.0. The best mAP performance was at the level @0.5 with score of 0.776 for all classes. Meanwhile, the mAP@0.5:0.95 was 0.573 for all classes, indicating that the model’s performance requires further improvement. Our study is promising as a guidance for future development of AI-based weed detection.

关键词： YOLO Training Electrical engineering Noise Training data Plantations Lighting Robustness Image augmentation information technology

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Determining single tuition fee of higher education in Indonesia: A comparative analysis of data mining classification algorithms

Determining single tuition fee of higher education in Indone...

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Conference on New Media Studies (CoNMedia)

作者： Muhammad Nur Yasir Utomo Adhistya Erna Permanasari Eddy Tungadi Irfan Syamsuddin Department of Electrical Engineering and Information Technology Universitas Gadjah Mada Yogyakarta Indonesia Computer and Network Engineering Study Program Politeknik Negeri Ujung Pandang Makassar Indonesia

ISBN: (纸本)9781509062850

Student's Single Tuition Fee or Uang Kuliah Tunggal (UKT) is a subsidy policy in higher education by the Indonesian government. This policy regulates the tuition fees incurred by each student at each semester in every higher education institutions. Since the cost of UKT expenses is influenced by the financial ability of each student, therefore the cost of education among students must be grouped into several classes. Until recently, there has been no standard to make such classification whereas such determination is an important task to solve by every higher institution in Indonesia. This study aims to compare five data mining classification algorithms (Gaussian Naïve Bayes, Multinomial Naïve Bayes, Bernoulli Naïve Bayes, Decision Tree and SVM) to find the best algorithm for the case of determining the UKT classes. The experiment is conducted using 230 training data and 10-fold cross-validation evaluation. Based on the result, Decision Tree managed to obtain average accuracy value of 0.814 or 81.4%. Finally, Decision Tree is used to classify the UKT classes of3258 data of students.

关键词： Classification algorithms Data mining Decision trees Support vector machines Economics Niobium Education

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