cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Paska Hasugian
Contact Email
infokum@seaninstitute.org
Phone
+6281264451404
Journal Mail Official
infokum@seaninstitute.org
Editorial Address
Komplek New Pratama ASri Blok C, No.2, Deliserdang, Sumatera Utara, Indonesia
Location
Unknown,
Unknown
INDONESIA
INFOKUM
Published by SEAN INSTITUTE
ISSN : 23029706     EISSN : 27224635     DOI : -
Core Subject : Science,
Computer Science & IT
The INFOKUM a scientific journal of Decision support sistem , expert system and artificial inteligens which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences. Software Engineering. Image Processing Datamining Artificial Neural Networks
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 7 Documents
 1 
Search results for , issue "Vol. 8 No. 2, Juni (2020): Data Mining, Image Processing and artificial intelligence" : 7 Documents clear
DESIGN OF DIGITAL IMAGE EDGE DETECTION APPLICATIONS USING FREI-CHEN ALGORITHM Leonardus Sitinjak
INFOKUM Vol. 8 No. 2, Juni (2020): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (474.279 KB)

Abstract

One image processing technique used is edge detection. Edge detection is a common thing in digital image processing because it is one of the first steps in image segmentation, which aims to present the objects contained in the image. Edge detection functions to identify the boundary lines of an object against overlapping backgrounds. Currently several methods can be used for edge detection, for example the Sobel, Canny, Prewitt, Frei-Chen, and SUSAN methods. In this research, 1 method is taken, namely the Frei-Chen algorithm. The results of this study indicate that this operator is successful in detecting edges in an image. When detecting edges in images containing noise the Frei-Chen algorithm is better at edge detection.
IMAGE EDGE DETECTION USING ROBINSON OPERATOR PANDI BARITA NAULI SIMANGSONG
INFOKUM Vol. 8 No. 2, Juni (2020): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (917.747 KB)

Abstract

Image processing is now widely used in almost all fields including medicine, industry, agriculture, geology, marine, and so on. One of the main things in image processing is the process of detecting the edge of an image, wherewith this process the boundary edge of an object with its background can be well determined. Edge detection is a method that can be used to detect the edge of an image that aims to improve the appearance of the boundaries of an area or objects in the image so that objects or boundaries of an area in the image are more easily recognized by humans and machines. Edge detection in digital images aims to recognize a pattern contained in the image itself. With the recognition of patterns in an image will be easily obtained information in an image. Determining the location of the edge of an image is easy if the condition of the image is clear and sharp, but the accuracy of the existence of the edge becomes difficult to determine if there is interference in the image, such as noise. But often it also results in an unsustainable image border where the results are influenced by the type of method used.
CANNY OPERATOR'S IMPLEMENTATION OF IMAGE SEGMENTATION Pristiwanto Pristiwanto
INFOKUM Vol. 8 No. 2, Juni (2020): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (895.648 KB)

Abstract

The process of segmentation in digital images that separates an object from the background or background can be obtained from the RGB value of each pixel in the digital image so that the object can be processed for other purposes. As technology develops in applications that process digital images, segmentation is becoming increasingly necessary. The results of segmentation must also be more accurate because if the results of segmentation are inaccurate it will affect the results of the next process. In general, the segmentation process is divided into three parts based on classification, by edge, and by region. the process starts with inputting a digital image and then the grayscale process is carried out. Next, choose the method then do the edge detection process with the Canny or Laplacian operator and finally the dilation procccess
IMPLEMENTATION OF APRIORI ALGORITHM IN DETERMINING THE LEVEL OF PRINTING NEEDS R. Mahdalena Simanjorang
INFOKUM Vol. 8 No. 2, Juni (2020): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (929.54 KB)

Abstract

Competition in the business world, especially in the increasingly difficult printing world, requires developers to find strategies to increase orders for printed products ordered. An increasing number of order data every day can be used to develop marketing strategies if processed correctly. A priori algorithms include the type of association rules in data mining. One of the stages of association analysis that attracts many researchers to produce efficient algorithms is the analysis of high-frequency patterns (frequent pattern mining). The importance of an association can be known by two benchmarks, namely: support and confidence. Support (support value) is the percentage of the combination of these items in the database, while confidence (certainty value) is the strength of the relationship between items in association rules.
ANALYSIS OF SERVICE SATISFACTION LEVEL USING ROUGH SET ALGORITHM Jonhariono Sihotang
INFOKUM Vol. 8 No. 2, Juni (2020): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (797.276 KB)

Abstract

Data mining Is a technique that combines traditional data analysis techniques with algorithms for processing large amounts of data. Data mining can be used to perform data analysis and find important patterns in data. Data mining will be a benchmark or reference for making data mining processing decisions that can be done with the Rough Set method. Rough Set Method is one of the methods above that allows us to make decisions in hotel services because in this method there are formulations or stages of problem mechanics and a Result (decision) of a combination that may occur from the criteria above. From the results (decisions) derived from the processed data mining, it can be used as a reference for decision making. The Rought Set Method is a mathematical technique developed since 1980.
ANALYSIS OF SAVE AND LOAN INFORMATION SYSTEM AT COOPERATIVE KARYA BAKTI PEMATANG SIANTAR Victor Pakpahan; Azwar Aliansyah Saragih
INFOKUM Vol. 8 No. 2, Juni (2020): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (339.101 KB)

Abstract

A savings and loan cooperative is a cooperative whose business activities are to collect and distribute funds to its members at low interest rates. This cooperative is also known as a credit cooperative where the management is carried out independently and democratically, and the members join voluntarily. There is also a mention that savings and loan cooperatives are non-bank financial institutions that have a business of accepting deposits from their members and providing loans to their members. The savings and loan information system at the Karya Bakti Pematang Siantar cooperative already exists and is already running in the data processing process, the application used is Visual Basic 6.0 as a programming language and MySQL as a database. Here the author will analyze the system and will build the system. The application used to build the system is XAMPP and the database uses MySQL. By analyzing existing information systems the author can find out whether the system that is running is good or not, and the author will build the system so that the system can run properly and efficiently.
Design a Blog Web Creation Application Using HTML 5 Rizaldy Khair; Ekatri Ayuningsih
INFOKUM Vol. 8 No. 2, Juni (2020): Data Mining, Image Processing and artificial intelligence
Publisher : Sean Institute

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

Abstract

The purpose of this study is to simplify the process of creating a weblog and provide solutions to compatibility problems in standalone applications. HTML5 is the latest web technology that continues to be developed and will soon be the successor of the previous generation of HTML. The web-based presentation creation service in question will utilize HTML5 and JavaScript features to present a user-friendly web-based application, with an emphasis on receiving input in the form of text and managing it into a web 2.0-based responsive blog. This web2.0 blog based on HTML 5 and CSS 3 provides a presentation creation interface with features such as automatic audio and video player without having to add additional plugins. In addition, this blog simplifies in the creation of coding.

Page 1 of 1 | Total Record : 7

 1 

Filter by Year

2020 2020


Reset
Filter By Issues
All Issue Vol. 11 No. 05 (2023): Engineering, Computer and Communication, Inpres Vol. 11 No. 04 (2023): Agustus : Engineering, Computer and Communication Vol. 11 No. 03 (2023): Juni : Engineering, Computer and Communication Vol. 11 No. 02 (2023): April, Engineering, Computer and Communication Vol. 10 No. 03 (2022): August, Data Mining, Image Processing, and artificial intelligence Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence Vol. 10 No. 5 (2022): December, Computer and Communication Vol. 10 No. 4 (2022): October, computer, information and engineering Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking Vol. 8 No. 2, Juni (2020): Data Mining, Image Processing and artificial intelligence Vol. 8 No. 1, Desembe (2019): Data Mining,Image Processing and artificial intelligence Vol. 7 No. 2, Juni (2019): Data Mining And Image Processing Vol. 7 No. 1, Desembe (2018): Data Mining And Image Processing More Issue