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Hybrid Encryption Based on Fernet and Rivest Shamir Adleman (RSA)

Hybrid Encryption Based on Fernet and Rivest Shamir Adleman ...

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

作者： Muhammad Dafi Hisbullah Christy Atika Sari Eko Hari Rachmawanto Lekso Budi Handoko Chaerul Umam Folasade Isinkaye Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Department of Computer Science Ekiti State University Ekiti Nigeria

RSA is an asymmetric encryption algorithm that uses two different keys, a public key to encrypt the plain text and a private key to decrypt the cipher text. Fernet is a symmetric encryption algorithm that uses a single key to encrypt and decrypt information. This study uses Fernet and RSA which is the combination of symmetric and asymmetric encryption called hybrid encryption. In addition, the cipher text will be hidden inside an image using Stepic. Hybrid Encryption uses asymmetric encryption to encrypt the symmetric encryption secret key, it will secure the symmetric encryption. The result of this study is the lowest error that we got as the MSE is 0.00% and is inversely proportional with the Peak Signal to Noise Ratio (PSNR) and Avalanche (AVA) with 79.00% and 42.34% in order. Inversely proportional to the length of the text that is hidden in the image, the longest text that is hidden, the more changes that we get in the image with the highest Unified Average Changing Intensity (UACI) and Number of Pixels Change Rate (NPCR) with the biggest image size with 46.48% for UACI and 99.86% for the NPCR.

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New Media as a Tools to Improve Creative Thinking: A Systematic Literature Review

New Media as a Tools to Improve Creative Thinking: A Systema...

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International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Hellik Hermawan Fajar Mahardika Irma Darmayanti R. Bagus Bambang Sumantri Dhanar Intan Surya Saputra Afrig Aminuddin Department of Informatics Faculty of Computer Science Universitas Amikom Purwokerto Banyumas Jawa Tengah Indonesia Computer Technology Study Program Faculty of Science and Technology Institut Teknologi dan Sains Nahdlatul Ulama Pekalongan Indonesia Department of Information technology Faculty of Computer Science Universitas Amikom Purwokerto Banyumas Jawa Tengah Indonesia Information Systems Study Program Faculty Of Science and Technology Universitas Harapan Bangsa Indonesia Faculty of Computer Science Universitas Amikom Yogyakarta Sleman Indonesia

This systematic literature review (SLR) study aims to analyze the role of New Media as a Tool to Improve Creative Thinking, with relevant articles from 2018 to 2023 taken from reputable international journals. It uses three research questions (RQ) to explore New Media's relevance in stimulating creativity. The results indicate that interactive platforms such as social media and online collaboration tools positively influence creative thinking skills. Interaction through New Media allows individuals to share ideas, discuss, and be exposed to various points of view, all of which stimulate creative thinking. In addition, New Media also facilitates the creative process of solving problems and generating original ideas. The immersive experiences offered by this technology can enhance the exploration of ideas and increase the ability to think out-of-the-box. While New Media offers great potential to enhance creativity, there are also potential risks, such as false information, media addiction, and privacy concerns. Therefore, awareness of the wise use of New Media needs to be increased, especially in education and everyday life. Overall, this literature review provides in-depth insight into the role of New Media in enhancing creative thinking skills and driving innovation. With the right approach, New Media can be an effective tool in stimulating creative thinking and encouraging the creation of original ideas beneficial for future social and technological developments.

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Scientometric Analysis of Artificial Intelligence Research in Agriculture 4

Scientometric Analysis of Artificial Intelligence Research i...

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

作者： Maulana, Fairuz Iqbal Pramono, Andi Hamim, Miftahul Prihatin, Sukeipah Yuli Arifuddin, Rahman School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia Binus Business School Bina Nusantara University Entrepreneurship Business Creation Jakarta11480 Indonesia Politeknik Kota Malang Informatics Study Program Malang Indonesia University of Merdeka Malang Department of Electrical Engineering Malang Indonesia

ISBN: (纸本)9781665473279

Artificial Intelligence Research in Agriculture has grown so common, and the potential they provide is so revolutionary that it is considered essential for competitive growth. Until we conducted this research, only 1064 academic documents on Trends of Artificial Intelligence Research in Agriculture that we found from 2012 to 2021 were obtained by searching the Scopus database. This study uses bibliometric analysis methods to map scientific publications worldwide. We use an article selection process, the year limitation, then the database is exported to RIS and CSV format files. Researchers in the United States had the most published articles and were indexed by Scopus among the most prolific authors ($\mathrm{N}=287$), followed by the United Kingdom at second ($\mathrm{N}=139$) and Italy with 66 academic publications. Data analysis reveals an increasing trend in the number of Trends of Artificial Intelligence Research in Agriculture publications worldwide, as measured by the Scopus index. © 2022 IEEE.

关键词： Agriculture

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Automatic Food Leftover Estimation in Tray Box Using Image Segmentation

Automatic Food Leftover Estimation in Tray Box Using Image S...

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International Conference on Sustainable Information Engineering and Technology (SIET)

作者： Yuita Arum Sari Ratih Kartika Dewi Jaya Mahar Maligan Anindya Sasri Ananta Sigit Adinugroho Computer Vision Research Group Faculty of Computer Science Malang Indonesia Mobile Game and Multimedia Research Group Faculty of Computer Science Malang Indonesia Food Nutrition Study Program Faculty of Agricultural Technology Malang Indonesia

Nutritional food is the most important aspect for people to fulfil their daily needs, but nowadays, the change of lifestyle can affect the style of food consumption, for instance leaving food when they take a meal. Besides, food leftover causes loss of consumed nutrients. We took an observation in a canteen in Faculty of Agricultural Technology in University of Brawijaya produces lost of food about 1,142.5 gram per day. To prevent the amount of food waste, this paper proposes an early stage framework to create an automatic leftover estimation method using image segmentation based on color channel. So that, we can optimize of the amount of food served and avoid loss food nutritions hereinafter. We experimented in two types of background of tray box: black and gray, then an automatic cropping process based on each sub area of tray box is implemented. Each part of them contains an item of food, so we detect the area using color channel segmentation and implements B component in LAB color space. After getting the main area of food, then two areas between segmented food image are compared before and after being consumed. The calculation of the predicted leftover portion is calculated based on original weight of food item. The result shows that tray box with black background with constant (cd) is the best to project leftover, in which reaches 2.37 of Root Mean Square Error (RMSE). It proves that the propose method is sufficient to handle the leftover prediction of food.

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Comparison of Online Learning Versus Face to Face Learning in English Grammar Learning

Comparison of Online Learning Versus Face to Face Learning i...

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International Conference on Computing, Engineering, and Design (ICCED)

作者： Anthony Anggrawan Abdul Hakim Yassi Christofer Satria Burhanuddin Arafah H. Mustafa Makka Computer Science study program of Bumigora University West Nusa Tenggara Indonesia Department of Linguistics University of Hasanuddin South Sulawesi Makassar Indonesia Visual Communication Design Study Program of Bumigora University West Nusa Tenggara Indonesia

ISBN: (数字)9781728120942

ISBN: (纸本)9781728120959

Online learning has shifted from being merely marginal trend to become popular in English language learning. Where, the number of higher education institutions has dramatically increased to offer English language learning using the online learning. Online learning has led to extremely changes in education generally and language learning in particular. At the same time, it is demanded to improve the learning outcomes of English by using technology effectively. The lack of attention to grammar was causing falling standards in language. So, the studies no longer address whether you need to learn English grammar or not, but how to choose a good way to learn English grammar to produce better learning outcomes. Consequently, research is necessary to examine whether the advantages of online learning apply to learning English grammar, especially in improving satisfactory learning outcomes. Therefore this study will conduct research on the effects of online learning on learning outcomes of English grammar. This study concluded that the learning outcomes of students who received English grammar online learning showed very good learning outcomes. Furthermore, students who are treated with online learning in English grammar learning provides better cognitive outcomes than students who attend face to face learning.

关键词： online learning English language language learning English Grammar learning outcome face to face learning e-learning Language Development English language learning outcomes syntax English Learning

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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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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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Eye Disease Detection Model Using Convolutional Neural Network with RMSprop, SGD, and Adam Optimizers

Eye Disease Detection Model Using Convolutional Neural Netwo...

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International Conference on ICT For Smart Society (ICISS)

作者： Dede Kurniadi Asri Mulyani Moch Riefky Rafliana Suwandy Department of Computer Science Institut Teknologi Garut Kabupaten Garut Indonesia Informatics Study Program Institut Teknologi Garut Kabupaten Garut Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

Eye disorders such as cataracts, glaucoma, and diabetic retinopathy can cause abnormalities in eye function, including blindness. This research aims to develop a machine-learning model and find the best model for detecting eye diseases. Deep Learning methods based on the Convolutional Neural Network (CNN) model will be used to create eye disease detection models by adding the RMSProp, SGD, and Adam optimizers techniques. The dataset used consists of 4 classes, namely normal (1074 data), glaucoma (1007 data), cataract (1038 data), and diabetic retinopathy (1098 data), totaling 4217 fundus images. The evaluation results reveal the CNN model with the RMSProp optimizer has better model performance with a value of 88% accuracy, 88% precision, 87% recall, and 88% f1-score, and based on the AUC value on the ROC-AUC curve for each class is above 0.90, which means that the model can differentiate data between classes well and is included in the Excellent classification category.

关键词： Glaucoma Cataracts Training Deep learning Diabetic retinopathy Accuracy Blindness Data models Convolutional neural networks

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Challenges on Cloud Computing Migration Strategy for Music Industry: A Systematic Literature Review

Challenges on Cloud Computing Migration Strategy for Music I...

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

作者： Hijir Della Wirasti Henki Seta Deden Witarsyah Hamonagan K Prabu Ayu Azzahro Bayu Hananto Faculty of Engineering Industry Telkom University Bandung Indonesia Informatics Study Program Computer Science Faculty Universitas Pembangunan Nasional Veteran Jakarta

Cloud computing has emerged as a transformative technology that offers numerous benefits to various industries, including the music industry. Cloud computing has revolutionized the way businesses operate and has had a significant impact on various industries, including the music industry Cloud computing, with its scalability, flexibility, and cost-effectiveness, presents an opportunity for the music industry to leverage technology to enhance its operations and meet the evolving demands of the digital era. This paper presents a systematic literature review on cloud computing migration strategies specifically tailored for the music industry. The review aims to identify existing research, frameworks, and best practices related to cloud migration in the music industry, as well as highlight the challenges and opportunities associated with such migrations. Through an analysis of relevant literature, this study provides valuable insights to assist music industry stakeholders in developing effective cloud migration strategies.

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Contemporary studies of task-technology fit: A review of the literature 6

Contemporary studies of task-technology fit: A review of the...

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6th International Conference on Information Management and Technology, ICIMTech 2021

作者： Hidayat, Desman Pangaribuan, Christian Haposan Putra, Okta Prihatma Bayu Irawan, Iwan Bina Nusantara University Binus Entrepreneurship Center Management Department Jakarta11480 Indonesia Sampoerna University Management Study Program Faculty of Business Jakarta12780 Indonesia Bina Nusantara University Binus Business School Undergraduate Program Management Departement Jakarta11480 Indonesia Character Building Development Center Computer Science Department Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

Information technology can influence task characteristics for the improvement of task performance. This review of the literature aims to explore the application of the TTF theory by exploring the scope and range of the available literature that applies the specific elements of the theory and summarizing and disseminating the research findings, specifically the environments where TTF has been applied. It was found that the education field is the most researched topic in TTF for the last three years, followed by social media, business, and management fields. Overall, the results of this study provide an understanding of applications of the theory and assists in providing avenues for future studies to investigate TTF studies further. © 2021 IEEE.

关键词： Social networking (online) Bibliographies Education Asia Developing countries Information management Task analysis

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