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All Journal KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) KAKIFIKOM : Kumpulan Artikel Karya Ilmiah Fakultas Ilmu Komputer Jatilima : Jurnal Multimedia Dan Teknologi Informasi INFOKUM JUKI : Jurnal Komputer dan Informatika MEANS (Media Informasi Analisa dan Sistem) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Jurnal ABDIMAS Budi Darma Ulead : Jurnal E-pengabdian JUDGE: Jurnal Hukum Multidisiplin Pengabdian Kepada Masyarakat (M-PKM) Transnational Business Law Journal Marsipature Hutanabe: Jurnal Pengabdian Kepada Masyarakat
Kristian Siregar
Universitas Budi Darma, Medan
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Other

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Journal : INFOKUM

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ANALYSIS OF IMPROVING DIGITAL IMAGE QUALITY USING ARITHMETIC MEAN FILTER ALGORITHM Mamed Rofendi; Kristian Siregar
INFOKUM Vol. 8 No. 1, Desembe (2019): Data Mining,Image Processing and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (616.018 KB)

Abstract

Image is a combination of points, lines, fields, and colors to create an imitation of a physical or human object. Digital imagery consists of square elements called pixels. An example of an image is an image. However, sometimes the image can also experience a decrease in quality (degradation). Images or pixels that have decreased image quality in image processing are called noise. This research discusses the enhancement of digital image quality using the Median filter technique to reduce noise. In this study using color image data (RGB) as test data and then converted into grayscale images to determine the gray degree of the image. The Grayscale image is stored in the database. Then noise is generated by using random numbers. The type of noise used is Salt & Pepper. Noise salt & pepper is a type of noise that has a value of 0 and 255 spread. To reduce noise salt & Pepper, an Arithmetic Mean Filter method or technique is used.
DIGITAL IMAGE COMPRESSION USING RUN LENGTH ENCODING METHOD Kristian Siregar
INFOKUM Vol. 7 No. 1, Desembe (2018): Data Mining And Image Processing
Publisher : Sean Institute

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Abstract

The application of Run Length Encoding (RLE) algorithm in image compression cannot always reduce the size of the image compression results. Giving a Run sign or the number of pixels that have repeated succession can certainly change the size of the image file to be smaller, but very different from the repetitive image pixels but not sequential or not at all will certainly give a large size change in the file compression Image compression files that use Algorithm RLE in applications that are often used by users in general on computers can read image matrices. Thus RLE has a special ability to reduce image files from the others if there is a composition of the value of repetitive image pixels. And to decompress RLE to digital images is also very simple because the file type .rle has information on the order of matrix values ​​consisting of two parts, the odd order is the pixel value for the image and while the even order is the value of the number of repeaters in the previous odd pixel value.
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

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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
TESTING THE C4.5 ALGORITHM WITH RAPID MINER TO DETERMINE DECISIONS FOR IMPLEMENTING SPORTS ACTIVITIES Siregar, Kristian
INFOKUM Vol. 11 No. 04 (2023): Agustus : Engineering, Computer and Communication
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v11i04.1790

Abstract

In the current era of information technology, decision making is an important aspect in various fields, including in the world of sports. The decision to carry out sports activities can be influenced by many factors such as weather conditions, availability of facilities, and the physical condition of the participants. With advances in technology and data science, there are algorithms that can assist in making these decisions. One of them is the C4.5 algorithm. This study aims to test the effectiveness of the C4.5 algorithm in determining decisions to carry out sports activities using the Rapid Miner software. The data used in this study is historical data from sports activities which include variables such as weather, date, and condition of the participants. The test results show that the C4. 5 is able to provide decisions with fairly high accuracy. By using Rapid Miner software, the process of learning and testing data becomes faster and more efficient. The conclusion of this study is that the C4.5 algorithm, with the help of Rapid Miner software, can be used as an effective method to assist in making decisions about sports activities.
Co-Authors , Sony Bahagia Sinaga Berry Richard Ornos Sinambela Denni M Rajagukguk Hasugian , Paska Marto Hery Sunandar Kennedi Tampubolon Mamed Rofendi Manalu, Mamed Rofendi Mesran, Mesran Monang Juanda Tua Sihombing Muhammad Syahrizal Panjaitan, Muhammad Iqbal Paska Miranda Sitanggang Pristiwanto Pristiwanto Pristiwanto Purba, Elvitrianim Riduansyah Riduansyah Riswan Limbong Sembiring, Abdul Sani Siagian, Edward Robinson Siddik Karo-Karo Tamba, RL Harmadi Tamba, RL. Harmadi Tamba, RL. Harmady Tarigan, Pilipus Tiepsi, Tiepsi Yasir Hasan