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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,
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INDONESIA
INFOKUM
Published by SEAN INSTITUTE
ISSN : 23029706     EISSN : 27224635     DOI : -
Core Subject : Science,
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
Articles 615 Documents
APRIORI ALGORITHM FOR THE DETERMINATION OF THE GOODS SALES MARKET BANK Fricles Ariwisanto Sianturi; Petti Indrayati Sijabat; Amran Sitohang; R. Mahdalena Simanjorang
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

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Abstract

Data mining a process of finding meaningful new relationships, patterns, and trends by filtering the huge data stored in the database using pattern recognition techniques. One of the data mining techniques is the a priori algorithm. A priori algorithm is defined as an algorithm for finding the highest frequency patterns. Currently, the a priori algorithm has been implemented in various fields, one of which is in the field of business or trade and the field of education. Market basket analysis technique or market basket analysis is a data mining technique that aims to find products that are often purchased simultaneously from transaction data. Bina Karya Swalayan is a modern market that has various types of goods. Where in the supermarket there are still some problems faced by a manager and employees
LOYALTY ASSESSMENT OF COMPANY COSTUMER WITH CLASSIFICATION METHOD Fricles Ariwisanto Sianturi; Jonson Manurung; R.Fanry Siahaan
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

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Abstract

Companies in general want the customers they have to be able to sustain forever. To make this happen is not something that is easy in the current climate of intense business competition, considering that there are rapid changes that can occur at any time, such as changes in customers, competitors and changes in broad conditions that are always dynamic. This requires policy makers to develop a strategy capable of achieving sales growth targets, increasing the company's market share. For this reason, an analysis of customer loyalty is needed. For this reason, an analysis is needed to understand and assess customer loyalty using a classification design method. With classification, information can be produced more quickly and the information presented is analytical in nature so that it is easy to use for decision making.
Decision Support System for Determining the Best Store Location at PT. Sumber Alfaria Trijaya Using the Ahp (Analytical Hierarchy Process) Method azlina Andriyani; Pristiwanto
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

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Abstract

DSS is designed to support all stages of decision making starting from identifying problems, selecting relevant data, determining the approach used in the decision-making process, to evaluating the selection. AHP is a decision support model developed by Thomas L. Saaty. This decision support model will describe a complex multi-factor or multi-criteria problem into a hierarchy, the hierarchy is defined as a representation of a complex problem in a multi-level structure where the first level is the goal, followed by the factor level, criteria, sub-criteria, and so on down to the last level of the alternatives. With a hierarchy, a complex problem can be broken down into groups which are then arranged into a hierarchical form so that the problem will appear more structured and systematic, in order to compete with several similar companies, PT. Sumber Alfaria Trijaya must be able to provide optimal service not only for consumers, but also for staff and employees so that they can work optimally. To be able to answer these challenges, the technology used must be able to balance the need for this. Because this company is engaged in retail, problems will arise both in the store, in the warehouse or in the system used.
EVALUATION OF THE K-NEAREST NEIGHBOR MODEL WITH K-FOLD CROSS VALIDATION ON IMAGE CLASSIFICATION M. Rhifky Wayahdi; Dinur Syahputra; Subhan Hafiz Nanda Ginting
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

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Abstract

In this paper, the data used is the banana image which is extracted into the dataset into 4 attributes, namely red, green, blue, and the mean for the classification process. Image data is classified using the k-Nearest Neighbor method which will be optimized the model with the k-Fold Cross Validation algorithm. Evaluation of the k-NN model with the k-FCV algorithm can improve accuracy and can build better machine learning models in the image classification process. The default K-NN obtained an accuracy rate of 57%, while the results of the model evaluation with the k-FCV algorithm, on fold 3 obtained an accuracy rate of 68%. The percentage yield with the new model increased by 11% which indicates that the machine learning model that was built was quite optimal
FUZZY TSUKAMOTO METHOD IN DETERMINING CORN QUALITY FOR ANIMAL FEED Dinur Syahputra; M. Rhifky Wayahdi; Subhan Hafiz Nanda Ginting
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

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Abstract

Animal feed is the largest cost component in the livestock industry. The existence of a solution to reduce the percentage of feed costs can have a tremendous positive impact for farmers. Animal feed is generally obtained by buying factory-produced animal feed that tends to be expensive or by making their own animal feed. However not all breeders can make their own animal feed because to make good feed the formulation process is. Fuzzy Tsukamoto is one of the fuzzy logic in which the methodology of the problem solving control system is suitable to be implemented on the system
IMPLEMENTATION OF SIMPLE ADDITIVE WEIGHTING (SAW) ALGORITHM IN DECISION SUPPORT SYSTEM FOR DETERMINING WORKING AREA FOR COOPERATIVE Subhan Hafiz Nanda Ginting; M. Rhifky Wayahdi; Dinur Syahputra
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

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Abstract

Today, the cooperative in Medan has difficulty in determining the work area for employees. The difficulty in determining the work area of ​​employees is because the number of employees does not meet the needs. In addition, the employees' lack of knowledge about the work area will be a problem. This has resulted in obstruction of the performance of employees at the Medan Cooperative. To overcome this problem, a decision support system is needed that can assist in making decisions to determine the employee's work area. Using the Simple Additive Weighting (SAW) method is expected to help companies to be able to assess and determine employees who meet the criteria and can work for a long time. The Decision Support System for selecting the work area that is currently being designed is the Decision Support System for Determining Work Areas in Cooperatives in Medan Using the Simple Additive Weighting (SAW) Method. Where with this system it can make it easier for companies to place employee work areas based on the area where the employee lives. The system designed can be used for all employees because it is very easy to use, no special computer skills are needed. So that employees can use this system to generate reports about their work area based on residence. Decision support system application designed using the Simple Additive Weighting (SAW) method at the Cooperative in Medan, can determine the work area of ​​employees.
DESIGN OF AUTOMATIC WATERING SYSTEM FOR HYDRAULIC PLANT MAINTENANCE USING MICROCONTROLLER BASED FUZZY SET METHOD Khairuna; Sriani; Adi Hartono; Abdul Halim Hasugian
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

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Abstract

The application of technology to agriculture provides an advantage in terms of increasing production or yields. In terms of maintaining a plant, it takes a long process, for example fertilizing, irrigation, synthesis of sunlight and others. Up to now, this work is still carried out by human labor so that it severely limits the yield or quantity of harvest. The application of technology for plant cultivation is planned to build an automatic irrigation system for hydroponic plants. Hydroponic plants are a type of plant that only need water in the process of growth. Thus a good irrigation system greatly affects the success of cultivating this type of plant. The results of this study are: First, designing a hydroponic plant maintenance system that works automatically with sensors and microcontrollers. Second, designing a control circuit using the ATMega8 Microcontroller as the system controller. And third, implementing the Fuzzy Set algorithm in the program so that the system can work properly.
EXPERT SYSTEM FOR TROUBLESHOOTING LAPTOP MOTHERBOARD DAMAGE USING FORWARD CHAINING METHOD AT BUDI DARMA UNIVERSITY COMPUTER LAB Hery Sunandar; Berto Nadeak; Pristiwanto; Saidi Ramadan Siregar
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

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Abstract

The development of laptop hardware technology in the 21st century is increasingly rapid to support information technology that is increasingly easily accessed. Laptops have an important role in helping human activities, especially in teaching and learning activities. Not infrequently a laptop or better known as a laptop as most students and lecturers and even students who sit in secondary education have started to use it. In national tertiary education, the entire campus requires both public and private universities to have laptop laboratories. Along with these developments in the case of laptop usage is getting bigger.
IMPLEMENTATION OF QUANTITATION TECHNIQUES TO PERFORM RGB IMAGE COMPRESSION Petti Indrayati Sijabat
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

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Abstract

the use of RGB images is a necessity in various fields. However, its use is constrained by the large file capacity, but it is possible to compress the images that are owned as needed. With the quantization method, the R matrix, G matrix and B matrix will be reduced in level, so that the number of bits used to represent the image is reduced. Because the number of bits is reduced, the file size becomes smaller. The quantization method is included in the Lossy Compression category, so that the compressed image cannot be decompressed again because there is missing information. Image compression is an image compression process that aims to reduce duplication of data in the image so that less memory is used to represent the image than the original image representation. There are factors why the image compression process is very appropriate so that there is no significant correlation between pixels and neighboring pixels
APPLICATION OF SPEED UP ROBUST FEATURES (SURF) AND FEATURES FROM ACCELERATED SEGMENT TEST (FAST) FOR INTRODUCTION OF PLACE Mhd. Furqan; Rakhmat Kurniawan; Mey Hendra Putra Sirait
INFOKUM Vol. 9 No. 1,Desember (2020): Data Mining, Image Processing,artificial intelligence, networking
Publisher : Sean Institute

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Abstract

With the current technology that is starting to develop rapidly, it can match an image with another image. In recognizing an image, there needs to be a process that will be carried out in image matching, but current image matching is still comparing pixels between two images. To compare between images, the color and resolution and shape of the image pixels affect the recognition results in an image. Therefore, to deal with this problem, the algorithms that can be used in the work process of this program are the Speed ​​Up Robust Features (SURF) algorithm and Features from Accelerated Segment Test (FAST). FAST is a method for determining the angle that is in an image while the SURF algorithm can describe the features that exist in an image so that image matching no longer matches between pixels but based on the descriptors that have been generated and the matched results will be listed on the database, using the SURF algorithm , there is no need to worry about the resolution, color, and shape of the image to be matched. Tests that were carried out were still successful with a precision value of 0.9, which means that the value of successful matching is 9% and with a recall value of 100% and a value that has reached 100% means that the number of points is similar to the number of points that have been matched

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