INFOKUM
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
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<![CDATA[CLASSIFICATION OF MAJOR SELECTION BASED ON STUDENTS EXPERTISE USING C4.5 ALGORITHM ]]>
<![CDATA[N P Dharshinni]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Selection and determination of majors is something that must be done by junior high school students when they want to enter senior high school. However, it is not uncommon for students to be confused in choosing the right major based on student expertise. The problems faced by many students who take majors because they follow their friends or parents and make it difficult for students to follow the available subjects according to the chosen majors and have an impact on student achievement. In analyzing the determination of the right major based on student expertise, the C4.5 algorithm is used. The classification of the C45 algorithm will produce a decision tree that can be used in determining the right direction. The results of the confusion matrix Classification of student value data in determining majors produce an accuracy value of 95.92%, class precision/class recall in Natural Sciences Major is 97.56%, class precision/class recall in Social Sciences Major is 87.50% and classification error is 4.08%. Decision tree results show the subject variables that influenced the selection of student majors were mathematics, science, ICT, skills, and tourism, The highest gain value lies in the Pariwista subject which is the root of the decision tree that is formed. The resulting rule is a math score above 82, a minimum science value of 84.5, a minimum ICT value of 85.5, so that students are more suitable for Natural Sciences Major. Meanwhile, if the value of mathematics is less than 82, tourism is less than 90.5 and skills are less than 84.5 then the student is more suitable for Social Sciences Major.]]>
<![CDATA[Combination of Euclidean Distance on X-Means Algorithm in Data Grouping ]]>
<![CDATA[Berti Sari Br Sembiring]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Grouping can use clustering to group data based on the similarity between the data, so that the data with the closest resemblance is in one cluster while the different data is in another group. The X-Means algorithm is the development of K-Means. The weakness of X-Means is that in determining the distance matrix, the distance matrix is an important factor that depends on the X-Means algorithm data set. The resulting distance matrix value will affect the performance of the algorithm. The results of the study are: testing with variations in the number of centroids (K) with values of 2,3,4,5,6,7,8,9,10. The author concludes that the number of centroids 3 and 4 has a better iteration value compared to the number of centroids that are getting higher and lower based on the iris dataset with the jarax matrix Manhattan Distance. From the test results with the X-Means cluster point, calculate the Euclidean Distance distance with 100 iris data reaching the 9th iteration, while with 100 iris data by calculating the Manhattan Distance distance it reaches the 10th iteration. Meanwhile, in determining the cluster point using the X-Means method from 100 data iris reaches its 7th iteration.]]>
<![CDATA[Analysis Algorithm Apriori in Medical Device Supply Planning ]]>
<![CDATA[Desilia Selvida]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[The application of the Apriori Algorithm helps in forming possible candidate item combinations, then testing whether the combination meets the minimum support and confidence parameters which are the threshold values given by the user. Even though until now, service activities and transactions at pharmacies have not experienced any significant problems, of course this situation will one day become an inhibiting factor in improving service as more and more transactions and types of items and transaction items are stored within a certain period of time, making it difficult for the pharmacy. in analyzing the types of items and itemset which consumers are most interested in or not interested in so that they can control the inventory of medical devices. The results of the study: The results of the pattern analysis above show that the greater value of support from a combination of medical devices provides recommendations for the medical devices most often purchased by consumers are thermometers, gauze, plaster, and elastic bandages. Conversely, the smaller the value of support for a combination of medical devices means that recommendations are given based on medical devices that are rarely purchased. The results of the application of the a priori method with a minimum support of 30% with a combination of 3 and 4 itemsets are if the thermometer, gauze, plaster, elastic bandages. The priori method used is quite effective in providing the final drug combination that is often purchased by consumers. The level of accuracy of the test using the a priori method is 100%.]]>
<![CDATA[Application of Expert System in Diagnosing Polycystic Ovary Syndrome ]]>
<![CDATA[Bahagia Tarigan]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[PCOS (Polycystic Ovary Syndrome) or polycystic ovary syndrome is a condition of impaired ovarian function in women of childbearing age. This condition causes the hormones of women suffering from PCOS to become imbalanced due to unknown reasons. The early signs of PCOS are irregular ovulation or fertility, increased levels of male hormones (androgens) in a woman's body, and the appearance of many cysts (fluid-filled sacs) on the ovaries. Things like that are very feared by women because women's nature is to conceive and have offspring, if it is not taken care of from the start or early on, it is not impossible for this to happen. But in fact, public knowledge is still low about Polycystic Ovary Syndrome, information about Polycystic Ovary Syndrome is still not well socialized to the public so that people still do not know how to handle and treat it. In diagnosing Polycystic Ovary Syndrome, there are several methods that can be used, including the Dempster Shafer method. From the results of the study, it can be concluded, among others: The expert system built can provide convenience for users to diagnose polycystic ovary syndrome, and can provide treatment solutions for the disease. The results of the diagnosis using the Dempster Shafer method have a better percentage value.]]>
<![CDATA[Analysis of AHP and SAW Methods in a Decision Support System for Determining Employee Positions ]]>
<![CDATA[Harianta Sembiring]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Employees are an important asset for every company, because they greatly affect many aspects that determine the success of the company's work. A company will be able to run all its business processes well if all its employees can be well organized by the HR (Human Resources) section. Placement and utilization of resources in the right position is absolutely necessary. In this case, proper management and utilization of resources plays a very important role because it is a strategic approach to improving organizational performance. Determination of employee positions is still not effective because the job analysis in the employee placement section is not carried out properly so that employees do not know for sure the work he is doing in the company. In addition, many employees are not experts in the field of work they hold so that what they do on a daily basis is not in accordance with their abilities. From the results of the study, it can be concluded, among others: The application of a decision support system that was built can provide convenience and minimize errors that may occur in the process of determining employee positions. criteria for determining employee positions. The level of accuracy of the test results is 97%.]]>
<![CDATA[DUAL TREE HUFFMAN ENCODING IMPLEMENTATION TO REDUCE LOW FREQUENCY BIT CODES ]]>
<![CDATA[Tommy Tommy]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Huffman encoding is a compression algorithm that uses symbol encoding using a simpler bit substitution based on the frequency of the symbol. A symbol will be represented with much fewer bits if it has a large frequency. Conversely, symbols with less frequency will be encoded with bits of greater length. The bit code for symbols with lower frequencies often has a very long size which sometimes causes the compressed file size to be larger than the original file. This study develops the implementation of two separate Huffman trees by dividing the symbol list into two lists, each of which will form a bit code in parallel. This implementation is able to minimize the length of the symbol bit code, especially in symbols with low frequencies so as to increase the compression ratio for several types of content which is become the weakness of the original Huffman.]]>
<![CDATA[Capacity Optimization On RGB Overlapping Block-Based Pixel Value Differencing Image Steganography With Adaptive Threshold ]]>
<![CDATA[Rosyidah Siregar]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Pixel value differencing steganography is an image steganography that utilizes the difference of the image pixel value to embed the secret message bits. RGB overlapped block-based PVD was introduced by Prasad and Pal which uses the difference value in the pair of RGB color components of a pixel compared to using the difference value of two consecutive pixels. This approach has good performance at increasing capacity especially in images with low pixel variance values. The RGB overlapped block-based PVD algorithm uses a threshold that limits the amount of difference in the color component pairs that are allowed to embed the secret message bits. The use of a global threshold will reduce the potential for optimal capacity utilization of the container image. This study implements an adaptive threshold that uses two different types of thresholds that use the embedding bit limit and the RMSE difference of the pixels before and after the embedding process to the next pixel. This optimization is able to provide a better capacity increase with PSNR degradation from the previous algorithm which is quite low.]]>
<![CDATA[Implementation of Topsis Method for Supervisor Selection Decision Making System at District 10 Restaurant And Bar ]]>
<![CDATA[Emasopangidoan Waruwu Emasopangidoan]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Management of Resources Manuasion of a company greatly influences many aspects of determining the success of the company. If the company's performance can be organized, all aspects of the company can run Good. The problem in District 10 Restaurant And Bar in choosing a supervisor is to use measurements based on the aspects and criteria desired and achieved by the company. So that in the process of selecting the pervisor only based on the direct behavior that is considered senior, but there is a fact that it cannot contribute more to the company and there is no specific method used in selecting Supervisors, so that the assessment is not appropriate. To overcome this problem, a computer system is needed that helps the Supervisor by using the Topsis Method TOPSIS (Technique for Others Reference to Ideal Solution). It will rank all alternatives to positive alternative solutions that have been ranked and then used as a reference for decision making, namely decision support system takes the decision to choose the best solution that is desired.]]>
<![CDATA[COMPUTER VISION IDENTIFICATION OF SPECIES, SEX, AND AGE OF INDONESIAN MARINE LOBSTERS ]]>
<![CDATA[Yasir Hasan]]>;
<![CDATA[Kristian Siregar]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[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]]>
<![CDATA[EXAMINE THE ROLE OF MOTIVATION IN UTAUT MODEL ON THE USE OF CLOUD COMPUTING BY SMEs DURING COVID-19 PANDEMIC ]]>
<![CDATA[Marwan Al Fajri]]>;
<![CDATA[Erwin Setiawan Panjaitan]]>;
<![CDATA[Hanes Hanes]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[The 2019 Corona Virus Disease (COVID-19) pandemic is affecting the business sector in Indonesia, especially Small and Medium Enterprise (SMEs) that contribute greatly to the economy which impacted on decrease in revenue due to health protocols. This study aims to examine the role of motivation in the use of cloud computing technology by SMEs during the pandemic by combining it with the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The research method uses quantitative data to test hypotheses that have been formulated through a survey of 129 SMEs in Medan using cloud computing technology since the pandemic. Questionnaires are distributed online and offline containing 25 indicators of variables arranged using the Likert scale. The data processing in this study used equation models from Structural Equation Modeling (SEM) and Smart Partial Least Square (SmartPLS) software. The results of this study received a positive response and showed a significant influence on motivation variable. SME actors have the motivation to survive in the sustainability of their business by using cloud computing technology as a necessity. So that the effect on the intention to use (behavior intention) to use cloud computing technology affects the actual use by SMEs.]]>
