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All Journal KAKIFIKOM : Kumpulan Artikel Karya Ilmiah Fakultas Ilmu Komputer Journal of Computer System and Informatics (JoSYC) INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) MEANS (Media Informasi Analisa dan Sistem) Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal ABDIMAS Budi Darma Bulletin of Data Science Ulead : Jurnal E-pengabdian JIKTEKS : Jurnal Ilmu Komputer dan Teknologi Informasi
Yasir Hasan
Universitas Budi Darma Medan
Agriculture, Biological Sciences & Forestry Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Other

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Journal : INFOKUM

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COMPUTER VISION IDENTIFICATION OF SPECIES, SEX, AND AGE OF INDONESIAN MARINE LOBSTERS Yasir Hasan; Kristian Siregar
INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (541.459 KB)

Abstract

Lobster in Indonesia consists of various types of colors, shapes, and habitats. Documentation results from several studies in the field of fisheries show the dynamics and richness of this type of shrimp species that have a hard and large skeleton. It is necessary to apply this knowledge to the field of information technology and computerization. The application that is right on target for the community is the application that is felt to be useful in the activities of the community itself. The application of information on lobster diversity found in Indonesia in the form of computer technology is to create a knowledge-based lobster recognition computer. This computer technology is designed as a computer vision identification of species, sex, and age of Indonesian water lobsters. Lobster identification is built with three levels of structure, namely the introduction of the type of lobster, the introduction of the sex of the lobster, and the introduction of the age of the lobster. The identification of lobster species here uses color recognition and edge detection techniques from lobster body image data that has been stored in a python-based value library file. For gender recognition using edge detection and pattern recognition techniques from image data of the bottom of the lobster such as the image of the legs. Meanwhile, for the introduction of lobster age, the technique of measuring the length of the lobster carapace distance was used. All these objects can be identified by the features provided by OpenCV in Python language
Steganography Test for Exif Metadata on JPEG Files With AES-256 Encryption for Secret Message Security Hasan, Yasir
INFOKUM Vol. 13 No. 05 (2025): Infokum
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v13i05.2967

Abstract

One of the main challenges is hiding secret messages in media such as JPEG images. However, embedding messages directly into EXIF metadata can pose detection risks and vulnerability to forensic analysis attacks, and this technique faces challenges in security, resistance to metadata manipulation, and message extraction accuracy. The method used in this study involves embedding a message encrypted using AES-256 ECB mode and Base64 into the EXIF metadata of JPEG files, so that only those with the decryption key can access the message content. This system is designed to be compatible with standard image processing software without changing the main structure of the JPEG file, making it difficult to detect by conventional metadata analysis techniques. Test results show that this method is able to embed secret messages with a high level of security without changing the visual quality of the image. AES-256 encryption encoded in Base64 is proven to be effective in maintaining the confidentiality of messages, so that only users with the correct decryption key can access them. Thus, the combination of EXIF metadata steganography and AES-256 encryption in Base64 provides an effective solution for securing secret messages in JPEG files, improving data protection against the threat of information theft and manipulation.
Co-Authors Gulo, Mentari Jun Efferi Hery Sunandar II, Ramadani Ikwan Lubis Kristian Siregar Mesran, Mesran Muhammad Yusuf Batubara Pristiwanto, Pristiwanto Sinaga, Sony Bahagia Sinaga, Sony Bahagia Zulkarnain Zulkarnain