1,720,982 research outputs found
An Advantage of Digital Book for Business Education in Indonesia Country
Get PDFThe main objective of this paper is to see the opportunity of a business education about digital book that consist of media education in Indonesia country. As we know the technology of a digital book for multimedia learning are still rare use by Indonesia educational teachers, the purpose is to determine the profit business in the future for making of digital book. The research design consisted of development design. The methodology analysis that will use in this research is SWOT (Strength, Weakness, Opportunity, Threats). The result of a research is finding that the business of digital book for learning tools in Indonesia country still open wide. Recommendations have been given on the basis of findings
An improved robust image watermarking by using different embedding strengths
Get PDFImage watermarking technique is an alternative solution to protecting digital image copyright. This paper proposed a new embedding technique based on different embedding strengths for embedding a watermark. An image is divided into non-overlapping blocks of 8 × 8 pixels. The variance pixel value was computed for each image block. Image blocks with the highest variance value were selected for the embedding regions. Therefore, it was transformed by discrete cosine transforms (DCT). Five DCT coefficients in the middle frequency were selected and the average of selected DCT blocks was calculated to generate different embedding strengths by using a set of rules. The watermark bits were embedded by using a set of embedding rules with the proposed different embedding strengths. For an additional security, the binary watermark was scrambled by using an Arnold Transform before it was embedded. The experimental results showed that the proposed scheme achieved a higher imperceptibility than the other existing schemes. The proposed scheme achieved a watermarked image quality with a PSNR value of 46 dB. The proposed scheme also produced a high watermark extracting resistance under various attacks
An efficient adaptive scaling factor for 4×4 DCT image watermarking
Get PDFThe imperceptibility and robustness properties of the watermarked image are the major requirements for maintaining the watermarked image similar to the original image and keeping the inserted watermark resistant under various attacks. In order to optimize the scaling factor for balancing between imperceptibility and robustness, this paper proposed a technique to generate scaling factors by considering the image content. The scaling factor is generated based on selected DCT coefficients of 4 × 4 DCT. The proposed watermarking can generate dynamic scaling factors for different DCT coefficients. The embedding regions are determined by using variance pixels, whereby the highest variance pixel was prioritised for the first embedding watermark. The watermark image pixels were scrambled by using an Arnold cat map before the watermark was embedded. This research uses 10 images from USC-SIPI image database to evaluate the effectiveness of the proposed watermarking. The experimental results showed that the proposed method improved the invisibility of the watermarked image with PSNR value of 45.38 dB rather than other watermarking schemes. The proposed watermarking showed superior performance against different types of attack
Adaptive scaling factors based on the impact of selected DCT coefficients for image watermarking
Get PDFImage watermarking technique aims at high imperceptibility of the embedded watermark with minimal distortion in the watermarked images. In frequency-domain, block-based Discrete Cosine Transform (DCT) is a popular method which can be improved by different scaling factors. This paper presents an adaptive scaling factor for selected DCT coefficients in image watermarking. The image blocks that have lowest pixel variances are chosen as the embedding locations. The optimal scaling factors for selected DCT coefficients on the middle frequencies are obtained by finding the best quality of images. The embedding process is performed using the obtained scaling factors. The proposed technique was investigated to verify the robustness and imperceptibility against various image-processing attacks. It is proved that our technique achieves higher robustness against noise addition, filter and compression than the existing schemes in most cases. Our technique produces greater imperceptibility than the existing schemes
Analysis of User Satisfaction and Preferences in Choosing a Digital Game Platform (Study Case: Steam vs Epic Games Store)
Get PDFIn the digital era, the gaming industry has expanded rapidly, influencing social, cultural, and economic aspects. This study examines user satisfaction and preferences between Steam and Epic Games Store using the End User Computing Satisfaction (EUCS) model. A quantitative approach with descriptive and explanatory methods was employed. The study aims to identify which technical factors most influence user satisfaction and preferences between Steam and Epic Games Store. Using the EUCS model, the research will provide insights for developers to enhance user experience and inform strategies for improving digital gaming platforms. The findings will contribute to understanding technical drivers of user behavior and offer recommendations for creating user-centered design strategies in the competitive gaming market. Data analysis reveals that Steam holds a significant advantage in Content, Ease of Use, and Timeliness, leading to higher satisfaction. Steam offers a broader game selection, better community features, and a more functional interface than Epic Games Store. Statistical tests confirm Steam’s superiority. The study concludes that users prefer platforms with richer content, better experiences, and more efficient update systems, providing strategic insights for platform developers to improve competitiveness and user satisfaction.In the digital era, the gaming industry has expanded rapidly, influencing social, cultural, and economic aspects. This study examines user satisfaction and preferences between Steam and Epic Games Store using the End User Computing Satisfaction (EUCS) model. A quantitative approach with descriptive and explanatory methods was employed. The study aims to identify which technical factors most influence user satisfaction and preferences between Steam and Epic Games Store. Using the EUCS model, the research will provide insights for developers to enhance user experience and inform strategies for improving digital gaming platforms. The findings will contribute to understanding technical drivers of user behavior and offer recommendations for creating user-centered design strategies in the competitive gaming market. Data analysis reveals that Steam holds a significant advantage in Content, Ease of Use, and Timeliness, leading to higher satisfaction. Steam offers a broader game selection, better community features, and a more functional interface than Epic Games Store. Statistical tests confirm Steam’s superiority. The study concludes that users prefer platforms with richer content, better experiences, and more efficient update systems, providing strategic insights for platform developers to improve competitiveness and user satisfaction
Phishing Detection on Ethereum Network menggunakan Metode Machine Learning
Get PDFThis study discusses phishing detection on the Ethereum network using machine learning methods, specifically Graph Convolutional Networks (GCNs) and Enhanced Graph Attention Networks (EGAT). The background of this research is based on the increasing number of phishing attacks in the blockchain ecosystem that can threaten the financial security of users. The research aims to analyze the incidence rate of phishing attacks and develop effective and efficient detection methods. The methodology includes data collection from Ethereum transactions and phishing activities, followed by feature extraction, machine learning model training, and evaluation using metrics such as accuracy, precision, recall, and F-score. The identified research gap is the lack of focus on early-stage phishing detection in the Ethereum network and the suboptimal performance of existing methods in recognizing complex transaction patterns. The results indicate that EGAT achieves an accuracy of 93.6%, outperforming GCNs, which reach 91.2%. The conclusion of this research is that the EGAT method is superior in detecting phishing activities, providing significant contributions to security in the Ethereum network
Evaluasi Komparatif Optimizer pada YOLOv8s untuk Deteksi Alfabet Bahasa Isyarat Indonesia (BISINDO)
No full textIndonesian Sign Language (BISINDO) serves as primary communication for 2.6 million hearing-impaired individuals inIndonesia, yet automatic recognition technology limitations create accessibility barriers. Previous studies lack systematicoptimizer comparisons in YOLOv8s for BISINDO alphabet detection. This study evaluates three optimizers (SGD, AdamW,Adam) on YOLOv8s to determine optimal configuration for best performance and consistency. Methods: Research employedYOLOv8s with pre-trained weights on 12,650 BISINDO alphabet images (70%-20%-10% split). Evaluation conducted through15 deterministic training sessions with five replications per optimizer using deterministic seed. Framework included Accuracy,mAP, Precision/Recall metrics, and confusion matrix analysis. Results: SGD demonstrated superior performance [email protected]:0.95 of 0.94244, precision 0.99188, and recall 0.99756, outperforming AdamW (0.94197) and Adam (0.93845). Alloptimizers achieved perfect consistency with standard deviation 0.0. Confusion matrix revealed 95% alphabet classes achieveddetection rates ≥85% with total error <0.3%. Conclusion: SGD represents optimal optimizer for BISINDO detection withperfect reproducibility providing solid foundation for benchmark reliability in sign language recognition.Bahasa Isyarat Indonesia (BISINDO) merupakan komunikasi utama 2,6 juta penyandang disabilitas pendengaran di Indonesia, namun keterbatasan teknologi pengenalan otomatis menimbulkan hambatan aksesibilitas. Penelitian sebelumnya belum melakukan perbandingan optimizer sistematis pada YOLOv8s untuk deteksi alfabet BISINDO. Penelitian ini mengevaluasi tiga optimizer (SGD, AdamW, Adam) pada YOLOv8s untuk menentukan konfigurasi optimal dengan performa dan konsistensi terbaik. Methods: Penelitian menggunakan YOLOv8s dengan pre-trained weights pada 12,650 images alfabet BISINDO (split 70%-20%-10%). Evaluasi dilakukan melalui 15 sesi pelatihan deterministik dengan lima replikasi per optimizer menggunakan deterministic seed. Framework mencakup metrik Accuracy, mAP, Precision/Recall, dan analisis confusion matrix. Results: SGD menunjukkan performa superior dengan [email protected]:0.95 sebesar 0.94244, precision 0.99188, dan recall 0.99756, mengungguli AdamW (0.94197) dan Adam (0.93845). Semua optimizer mencapai konsistensi sempurna dengan standard deviation 0.0. Confusion matrix mengungkapkan 95% kelas alfabet mencapai detection rate ≥85% dengan total error <0.3%. Conclusion: SGD merupakan optimizer optimal untuk deteksi BISINDO dengan perfect reproducibility memberikan foundation solid untuk benchmark reliability dalam sign language recognition
Penerapan Visualisasi 3D dengan Autodesk Maya : Modelling - UV Mapping - Texturing
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Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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