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All Journal Jurnal Masyarakat Informatika Bulletin of Electrical Engineering and Informatics Scientific Journal of Informatics JAIS (Journal of Applied Intelligent System) Sinkron : Jurnal dan Penelitian Teknik Informatika Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Journal of Innovation Information Technology and Application (JINITA) Jurnal Teknik Informatika (JUTIF) Scientific Journal of Informatics
Doheir, Mohamed
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering

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Journal : Scientific Journal of Informatics

 1 
A Comparison of Non Blind Image Watermarking Using Transformation Domain Kartikadarma, Etika; Udayanti, Erika Devi; Sari, Christy Atika; Doheir, Mohamed
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In digital image processing, there is an algorithm that is most often used because it has advantages in imperceptibility and robustness. The DCT and HWT algorithms are usually used together to get better results. However in this study we wanted to know which of the algorithms had the better results for image processing by comparing these two algorithms for blind watermarking as the prevention of image plagiarism. The results of this study indicate that HWT has better results for image processing, especially blind watermarking because the results with MSE, PSNR, and NC show that HWT has advantages in every aspect. Using 512x512 pixels grayscale image as cover image, the MSE result from HWT is 0.0004156 with PSNR 81.9440 better than MSE from DCT 0.003 with PSNR 73.2949. On the other hand, robustness aspect has been tested using NC. DCT has good NC than HWT only in JPEG compression attack with value is 1, while another attack has better NC in HWT that yield close to 1.
A Comparison of Non Blind Image Watermarking Using Transformation Domain Kartikadarma, Etika; Udayanti, Erika Devi; Sari, Christy Atika; Doheir, Mohamed
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.28334

Abstract

Purpose: This study aims to know which of the algorithms had the better results for image processing by comparing these two algorithms for blind watermarking as the prevention of image plagiarism. Methods: The DCT and HWT algorithms used to get better results. Result: The results of this study indicate that HWT has better results for image processing, especially blind watermarking because the results with MSE, PSNR, and NC show that HWT has advantages in every aspect.  using 512x512 pixels grayscale image as cover image, the MSE result from HWT is 0.0004156 with PSNR 81.9440 better than MSE from DCT 0.003 with PSNR 73.2949. Novelty: Robustness aspect has been tested using NC. DCT has good NC than HWT only in JPEG compression attack with value is 1, while another attack has better NC in HWT that yield close to 1.
Histogram of Gradient in K-Nearest Neighbor for Javanese Alphabet Classification Susanto, Ajib; Atika Sari, Christy; Mulyono, Ibnu Utomo Wahyu; Doheir, Mohamed
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.30788

Abstract

Purpose: The Javanese script generally has a basic script or is commonly referred to as the “carakan” script. The script consists of 20 letters with different levels of difficulty. Some letters have similarities, so research is needed to make it easier to detect the image of Javanese characters. Methods: This study proposes recognizing Hiragana's writing characters using the K-Nearest Neighbor (K-NN) method. In the preprocessing stage, the segmentation process is carried out using the thresholding method to perform segmentation, followed by the Histogram of Gradient (HOG) feature extraction process and noise removal using median filtering. Histogram of Gradient (HoG) is one of the features used in computer vision and image processing in detecting an object in the form of a descriptor feature. There are 1000 data divided into 20 classes. Each class represents one letter of the basic Javanese script. Result: Based on data collection using the writings of 50 respondents where each respondent writes 20 basic Javanese characters, the highest accuracy was obtained at K = 1, namely 98.5%. Novelty: Using several preprocessing such as cropping, median filtering, otsu thresholding and HOG feature extraction before do classification, this experiment yields a good accuracy.
Capital Optical Character Recognition Using Neural Network Based on Gaussian Filter Astuti, Erna Zuni; Sari, Christy Atika; Syabilla, Mutiara; Sutrisno, Hendra; Rachmawanto, Eko Hari; Doheir, Mohamed
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.43438

Abstract

Purpose: As digital technology advances, society needs to convert physical text into digital text. There are now many methods available for doing this. One of them is OCR (Optical Character Recognition), which can scan images [1]–[4] containing writing and turn them into digital text, making it easier to copy written text from an image. Text recognition in images is complex due to variations in text size, color, font, orientation, background, and lighting conditions.Methods: The technique of text recognition or optical character recognition (OCR) in images can be done using several methods, one of which is a neural network or artificial neural network. The artificial neural network method can help a computer make intelligent decisions with limited human assistance. Intelligent decisions can be made because the neural network can learn and model the relationship between nonlinear and complex input and output data. In this research, the scaled conjugated gradient is applied for optimization. SCG is very effective in finding the minimum value of a complex function, but it takes longer than some other optimization algorithms.Result/Findings: The dataset used is an image with a size of 28 x 28 which is changed in dimension to 784 x 1. This research uses 4000 epochs and obtained the best validation result at epoch 3506 with a value of 0.0087446. Results: From the statistical test results, the effect of perceived usefulness on ease of use has the highest level of influence, obtaining a test value of 3.6. Furthermore, the effect of the attitude towards using on the behavioral intention to use has the lowest level of influence, which obtained a test value of 1.2.Novelty:  In this article, Gaussian filter is used as feature extraction to improve yield. Character detection results using a Gaussian filter are known to be almost 10% higher than those using only a neural network. The result with the Neural Network alone is 82.2%, while the Neural Network-Gaussian Filter produces 92.1%.
Co-Authors Abdussalam Abdussalam, Abdussalam Adi Sucipto, Adi Agustina, Feri Ajib Susanto Cahaya Jatmoko Christy Atika Sari Eko Hari Rachmawanto Elkaf Rahmawan Pramudya Erika Devi Udayanti Erna Zuni Astuti Etika Kartikadarma Fredricka, Jhoanne Guruh Fajar Shidik Heru Lestiawan Islam, Hussain Md Mehedul Kusumawati, Yupie Mulyono, Ibnu Utomo Wahyu Nugroho, Widhi Bagus Pamungkas, Caroko Aji Pratama, Zudha Pulung Nurtantio Andono Purwanto Purwanto Ramadhan Rakhmat Sani Rohmayani, Dini Sania, Wulida Rizki Setiarso, Ichwan Sinaga, Daurat Sugianto, Castaka Agus Suprayogi Suprayogi Sutrisno, Hendra Syabilla, Mutiara Syafira, Zahra Ghina