D
De Rosal Ignatius Moses Setiadi
Publications - 148
Citations - 1556
De Rosal Ignatius Moses Setiadi is an academic researcher. The author has contributed to research in topics: Encryption & Steganography. The author has an hindex of 18, co-authored 126 publications receiving 898 citations.
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Journal ArticleDOI
Review of automatic text summarization techniques & methods
Adhika Pramita Widyassari,Supriadi Rustad,Guruh Fajar Shidik,Edi Noersasongko,Abdul Syukur,Affandy Affandy,De Rosal Ignatius Moses Setiadi +6 more
TL;DR: This paper provides a broad and systematic review of research in the field of text summarization published from 2008 to 2019 and describes the techniques and methods that are often used by researchers as a comparison and means for developing methods.
Proceedings ArticleDOI
Tomatoes classification using K-NN based on GLCM and HSV color space
Oktaviana Rena Indriani,Edi Jaya Kusuma,Christy Atika Sari,Eko Hari Rachmawanto,De Rosal Ignatius Moses Setiadi +4 more
TL;DR: The proposed method can achieve the highest accuracy and can be classified to determined the maturity level of tomatoes by using K-Nearest Neighbour (K-NN) one of basic and simple classification method which utilizes the distance as a comparison of the similarity level of the image.
Journal ArticleDOI
Secure Image Steganography Algorithm Based on DCT with OTP Encryption
TL;DR: Combined steganography using discrete cosine transform (DCT) and cryptography using the one-time pad or vernam cipher implemented on a digital image obtained satisfactory results with PSNR and NCC high and resistant to JPEG compression and median filter.
Journal ArticleDOI
An Enhanced LSB-Image Steganography Using the Hybrid Canny-Sobel Edge Detection
TL;DR: In this research paper, Canny and Sobel detectors are combined to get a wider edge area for greater payload of messages while maintaining imperceptibility of stego-images.
Proceedings ArticleDOI
Face Recognition using FaceNet (Survey, Performance Test, and Comparison)
Ivan William,De Rosal Ignatius Moses Setiadi,Eko Hari Rachmawanto,Heru Agus Santoso,Christy Atika Sari +4 more
TL;DR: This research aims to conduct surveys, test performance, and compare the accuracy of the results of recognizing the face of the FaceNet method with various other methods that have been developed previously, and showed excellent results and was superior to other methods.