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

作者： Ade Cahyo Priyo Utomo Christy Atika Sari Eko Hari Rachmawanto Heru Pramono Hadi Salama A. Mostafa Wisam Subhi Talib Al-Dayyeni Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Study Program in Information Systems University of Dian Nuswantoro Semarang Indonesia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia School of Information Technologies and Engineering ADA University Baku Azerbaijan

Citrus Limon L. (Lemon) is a type of fruit that is currently widely consumed, because it contains abundant vitamin C, fiber, and antioxidants. This fruit have high potential in the agribusiness sector and is widely cultivated by traditional farmers. However, during harvest time, traditional farmers generally still use manual methods using the human eye in distinguishing the maturity level of lemons which is less efficient because it has a low accuracy. Digital image processing is one solution to this problem. In the research on the classification of lemon maturity levels using digital image processing with the feature extraction method of the Mean RGB, HSV, and LBP methods and the K-Nearest Neighbor classification algorithm in this study, a total of 120 lemon images were used which were divided into 80 training image data and 40 image data. testing. The results of model performance measurements in the form of the highest accuracy level in the Mean RGB method of 100%, the highest accuracy in the HSV method of 98%, and the highest accuracy in the LBP method of 82.5%.

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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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Comprehensive Analysis and Remediation of Insecure Direct Object References (IDOR) Vulnerabilities in Android APIs

Comprehensive Analysis and Remediation of Insecure Direct Ob...

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Cryptography, informatics, and Cybersecurity (ICoCICs), IEEE International Conference on

作者： Semi Yulianto Roni Reza Abdullah Benfano Soewito Computer Science Department Binus Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Informatics Engineering National Institute of Science and Technology Jakarta Indonesia Computer Science Department Binus Graduate Program. Master of Computer Science Bina Nusantara University Jakarta Indonesia

The escalating visibility of secure direct object reference (IDOR) vulnerabilities in API security, as indicated in the compilation of OWASP Top 10 API Security Risks, highlights a noteworthy peril to sensitive data. This study explores IDOR vulnerabilities found within Android APIs, intending to clarify their inception while evaluating their implications for application security. This study combined the qualitative and quantitative approaches. Insights were obtained from an actual penetration test on an Android app into the primary reasons for IDOR vulnerabilities, underscoring insufficient input validation and weak authorization methods. We stress the frequent occurrence of IDOR vulnerabilities in the OWASP Top 10 API vulnerability list, highlighting the necessity to prioritize them in security evaluations. There are mitigation recommendations available for developers, which recognize its limitations involving a possibly small and homogeneous selection of tested Android applications, the testing environment that could cause some inaccuracies, and the impact of time constraints. Additionally, the study noted insufficient threat modeling and root cause analysis, affecting its generalizability and real-world relevance. However, comprehending and controlling IDOR dangers can enhance Android API security, protect user data, and bolster application resilience.

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Digital Technology in Health Education Trend Mapping through Bibliometrics Analysis

Digital Technology in Health Education Trend Mapping through...

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International Conference on informatics, Multimedia, Cyber and Information System (ICIMCIS)

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

ISBN: (纸本)9781665473286

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.

关键词： Training Pediatrics Instruments Education Bibliometrics Transportation Psychology

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Decision Support System To Determine The Student Achievement Scholarship Recipients Using Fuzzy Multiple Attribute Decision Making (FMADM) With SAW

Decision Support System To Determine The Student Achievement...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Helmi Kurniawan Ashari P Swondo Eka Purnama Sari Khairul Ummi Yufrizal Fhery Agustin Faculty of Engineering and Computer Science Universitas Potensi Utama Medan Indonesia English Education Study Program Universitas Potensi Utama Medan Indonesia Manajement Study Program Universitas Potensi Utama Medan Indonesia

Higher education is an education unit that organizes higher education. College students are called students, while college educators are called lecturers. Higher education as a place of learning and self-development Students provide facilities to improve student achievement in the form of student achievement scholarships. This scholarship program is expected to stimulate students' interest in learning to be better. In determining scholarship recipients, the student division selects prospective scholarship recipients based on existing criteria. In the selection process, the student division has difficulty choosing the data of prospective recipients. Because each type of scholarship criteria and has different criteria weights. Calculation of the value of weighting criteria requires precision. Based on the problems that occur, the author designed a decision support system to determine the recipients of achievement scholarships using the SAW method. This system can help student affairs to carry out criteria for recipients of achievement scholarships based on administrative data of prospective scholarship recipients in determining criteria for weighting value calculations. With this system, it can minimize errors to determine prospective scholarship recipients who excel. After testing the use of support systems for deciding scholarship decisions using the SAW method, it can be concluded that a decision support system can assist the student's part in carrying out their duties.

关键词： Scholarships Surface acoustic waves Decision support systems Additives Decision making Analytical models

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Twenty years of e-learning in health science: A bibliometric

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Procedia computer science 2023年 216卷 604-612页

作者： Fairuz Iqbal Maulana M. Aldiki Febriantono Dwi Risza Budi Raharja Khaeruddin Ridho Herasmara Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Indonesia Electrical Engineering Faculty of Science and Technology Raden Rahmat Islamic University Malang Indonesia

Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conventionally. Supposedly with the advancement of technology and the use of the internet everywhere, learning such as e-learning can be important, especially in the health sector. Until this research was conducted, only 514 academic documents about e-learning in health sciences were found for 20 years from 2001 to 2020, obtained in searching on the Scopus database. This study presents a comprehensive overview of studies related to E-learning in the Health sciences sector. This study uses bibliometric analysis and indexed digital methods to map scientific publications throughout the world. This research employs the Scopus database to gather information, as well as the Scopus online analysis tool and Vosviewer to show the bibliometric network. The method consists with five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. Among the most published and indexed articles by Scopus, papers published by researchers in the United States have the highest number of publications (80), followed by United Kingdom (63) and Australia with 45 academic publications. The processed data shows the pattern and trend of increasing the number of international publications in E-learning in Health sciences field, which Scopus index.

关键词： e-learning health science bibliometric vosviewer education

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Hand-Woven Fabric Motif Recognition Methods: A Systematic Literature Review

Hand-Woven Fabric Motif Recognition Methods: A Systematic Li...

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International Conference on informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Handrie Noprisson Ermatita Ermatita Abdiansah Abdiansah Vina Ayumi Mariana Purba Marissa Utami Doctoral Program in Engineering Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia Program of Informatics Management Politeknik Anika Palembang Indonesia Faculty of Engineering Muhammadiyah University of Bengkulu Bengkulu Indonesia

ISBN: (纸本)9781665427340

Knowledge of hand-woven motif recognition is only owned by the older generation, which has not been passed down to the younger generation. Moreover, computer technology can be used to support the recognition of traditional woven fabric motifs. The aim of this research is to conduct a literature review on hand-woven fabric motif recognition, with an emphasis on performance accuracy, techniques, and datasets utilized. This research included three distinct stages of systematic literature review (SLR): planning, execution, and reporting of findings. We found several datasets between 924,845 data and the number of classes between 3–25 class. Based on research result, we obtained several methods for hand-woven fabric motif recognition focused on performance examination. We recommended image pre-processing method, including Adaptive Filtering Denoising, Adaptive Wiener Filtering, Histogram Equalization, Gradient Pyramid (GP) Decomposition. Moreover, we suggested five feature extraction methods, including Radon Transform, Wavelet Transform, Locally Rotation Invariance Measure (LBP-ROR), Transform Invariant Low-Rank Textures (TILT) and Histogram of Oriented Gradients (HOG). For learning method, we recommend Fuzzy C-Mean (FCM), Convolutional neural network (CNN), Deep Neural Network (DNN), MobileNets, Inception-v3 and ResNet-50.

关键词： Wavelet transforms Histograms Wiener filters Systematics Bibliographies Neural networks Fabrics

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Aircraft Flight Schedule Announcement at Pionir Indonesian Airport Based on SMS Broadcast

Aircraft Flight Schedule Announcement at Pionir Indonesian A...

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Aerospace Electrical engineering and informatics (ICAAEEI), International Conference of Adisutjipto on

作者： Anggraini Kusumaningrum Septian Wahyu Ahmad Sahal Asih Pujiastuti Astika Ayuningtyas Elizabeth Anna Pratiwi Informatics Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia Informatic Engineering Department Adisutjipto College of Technology Yogyakarta Indonesia D3 Information Technology Study Program Faculty of Science and Technology Respati University Yogyakarta Indonesia Aerospace Engineering Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia

ISBN: (数字)9798331507930

ISBN: (纸本)9798331507947

The design and construction of delivering announcements using a web-based SMS gateway aims to help overcome problems that often occur at pioneer airports; this is because when passengers want to travel, many passengers still arrive late to check-in, even though the passenger ticket has a notification for checking. -in 1 hour before Departure. If a flight's Departure is delayed or accelerated, passengers will only receive this information when they arrive at the airport, whereas if at the time the departure notification is delayed or accelerated, the passenger is still outside the airport or still on their way to the airport, as a result, they will definitely not receive the information. Testing voice announcements on parking, arrival, departure, delay, check-in, and waiting room services, as well as testing SMS broadcasts (30 user numbers and one airline), shows that the announcement application provides information through voice data recording and broadcasts SMS to passengers and families. Testing was carried out at Indonesian Pioner airport for 30 passengers for a week. The percentage of Ease of obtaining test voice information was 81.98%, and the percentage of Ease of obtaining broadcast SMS information was 83.1%. Implementing the announcement is feasible at pioneer airports with a percentage of 82.54%.

关键词： Electrical engineering Schedules Logic gates Airports Recording Delays informatics Aircraft Testing Airline industry

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Integration of Artificial Intelligence in Software Defined Networking Technology through Developing Machine Learning Algorithms 3

Integration of Artificial Intelligence in Software Defined N...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Naibaho, Lamhot Saxena, Pulkit Raj Sharma, Kuldeep Alfurhood, Badria Sulaiman Pallavi, L. Pant, Bhasker Faculty of Letters and Languages Christian University of Indonesia English Language Education Study Program Indonesia Teer Thanker Mahaveer University College of Computing Science and Information Technology Uttar Pradesh Moradabad India Lovely Professional University Department of Computer Science and Engineering Punjab Jalandhar Phagwara India College of Computer Information Sciences Princess Nourah Bint Abdulrahman University Department of Computer Sciences Saudi Arabia B v Raju Institute of Technology Cse Telangana Narsapur India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350399264

A future networking design called "software-defined networking"combines network programmability with centralized administration (SDN). Network administration is currently handled by SDN, which, at the regulator, which acts as the cable network processor and divides the data plane into a control plane and a data aircraft. Recent breakthroughs in artificial intelligence (Al) have shown a stronger inclination for the science community to benefit from their ability to give learning capabilities and enhance Indicator. The author of this research provides a comprehensive analysis of initiatives underway to incorporate Al with SDN. The study concluded that the three primary Al thread where scientific research was centered were computer science, conceptual, and fuzzy reasoning systems. The authors of this paper explore the several fields in which these approaches may be used, their potential future applications, and the innovations made possible by the integration of AI-based methods into the SDN paradigm. By choosing the right SDN controller, any large organization may lower network complexity, implementation expenses, and maintenance costs. The focus of this article is software defined networking's benefits and downsides (SDN). Following is a basic explanation of artificial intelligence and a list of some of its most significant applications in SDN. © 2023 IEEE.

关键词： Software defined networking

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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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