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 615 Documents
 3   4   5   6   7 
IMPLEMENTATION OF EXPERT SYSTEM TO IDENTIFY FORMALIN AND BORAX CONTENT IN FOOD USING THE CERTAINTY FACTOR METHOD Lisa Pristiwani Hasibuan; Volvo Sihombing; Muhammad Halmi Dar
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 (527.028 KB)

Abstract

Today, along with the times that are supported by the rapid development of technology, all aspects of life cannot be separated from the influence of technology. In terms of food, it is also supported by the role of women, nowadays women are born not only to take care of the household, but also to become women who earn big or often called career women, so that there is almost no time to prepare food for the family, so it is not surprising that food Fast food is preferred as one of the main alternatives to filling the stomach considering the taste of the food served and the serving time is only a matter of minutes so it doesn't waste a lot of time. However, without realizing it, some types of fast food that are often consumed contain several types of harmful ingredients that trigger the onset of chronic diseases, such as: heart attack, insulin resistance, diabetes, and several other dangerous diseases. Seeing this impact, so the author is interested in making an expert system application to identify the content of formalin and borax in food. In drawing conclusions in expert systems, Forward Chaining and Backward Chaining are generally used. However, with the use of these two reasons, it is not possible to determine the value of confidence in the hypothesis. So that the expert system can do reasoning like an expert even in conditions of data uncertainty and to get a confidence value in this case the author uses a method to solve the data using the Certainty Factor (CF) method. The Certainty Factor method is a method that defines a measure of certainty against a fact or rule, to describe the level of expert confidence in the problem at hand,
IMPLEMENTATION OF THE RUP METHOD ON THE LABUHAN BATU UNIVERSITY STUDENT ACTIVITY UNIT INFORMATION SYSTEM Siti Aisah Siregar; Deci Irmayani; Muhammad Halmi Dar
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 (625.083 KB)

Abstract

The Student Activity Unit (UKM) is a place where students who have the same interests and hobbies gather in a university. Univ. Labuhan Batu is a private university in Rantau Prapat which has 5 SMEs, at the time of registration, prospective SME members visit the UKM booths that have been opened by UKM management, besides that there are several other obstacles such as UKM Univ. Labuhan Batu is recorded manually only from the Student side of the Univ. Labuhan Batu, which contains the name of the PIC, date of activity, number, name of SME, place, start, finish, a number of attendance, meeting to, information, also material data that is not neatly arranged, as well as monthly report collection. In order to support the recording of activities in terms of attendance, members, and materials taught to the registration of SME members, the researchers created a web-based SME information system using the Rational Unified Process method, in this study using black-box testing. RUP is a method that uses the concept of object-oriented and has activities that focus on model development using the Unified Modeling Language (UML). The result of this research is an information system that can be used by SMEs, SME members, and the student body of Univ. Labuhan Batu makes it easy to collect attendance information, member data, activity data, materials, and announcements. and has activities that focus on model development using the Unified Modeling Language (UML). The result of this research is an information system that can be used by SMEs, SME members, and the student body of Univ. Labuhan Batu makes it easy to collect attendance information, member data, activity data, materials, and announcements. and has activities that focus on model development using the Unified Modeling Language (UML). The result of this research is an information system that can be used by SMEs, SME members, and the student body of Univ. Labuhan Batu makes it easy to collect attendance information, member data, activity data, materials, and announcements.
ANALYSIS OF THE ELECTRE METHOD IN DECISION SUPPORT SYSTEMS FOR DETERMINING AREAS OF EXPERTISE FOR INFORMATICS MANAGEMENT STUDY PROGRAM STUDENTS Sugih Hati Musti; Deci Irmayani; Gomal Juni Yanris
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 (560.017 KB)

Abstract

Confusion of students in concentrating on the field of science in the Informatics Study Program Univ. Labuhan Batu becomes a problem for students in writing a thesis. Informatics Engineering Study Program Univ. Labuhan Batu has a group of experts that is intended to direct students' thesis titles according to their fields. Elimination Choice and Translating Reality (ELECTRE) is the method used in this study. The ELECTRE method is a method that can produce decisions by comparing alternatives in pairs on the same criteria. The results obtained from this application are to provide a recommendation value in the form of a ranking based on the relationship between the alternatives and the criteria entered. The purpose of this research is to produce recommendations for areas of expertise for students of the Informatics Study Program Univ. Stone Labyrinth. System testing is done in two ways, namely black box testing and accuracy testing. Black box testing is done to test the functionality of the application based on the input entered. While the accuracy test is to see how much accuracy or suitability of the skill group students has with the results of the system recommendations.
IMPLEMENTATION OF APRIORI ALGORITHM IN PREDICTING CAR PARTS Syahman Putra Pratama Nst; Ibnu Rasyid Muthe; Rahma Mutiah
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 (843.256 KB)

Abstract

In the procurement of spare parts for the car production process, information or knowledge related to auto parts is needed so that the company's production processes and results are effective and efficient. The purpose of this study is to apply an a priori algorithm for prediction of auto parts that often appear. The research subject used is the BMW car production data of PT Gaya Motor. The research model used is market basket analysis. The stages of the research carried out include: (1) Data Collection; (2) Training Data; (3) Formation of Association Rule, (4) Lift Ratio Test, and (5) Drawing Conclusion. The research results obtained are the most widely produced BMW car types in 2018 are the BMW 320 and BMW 7 Series. So the company can use these results to determine strategies related to the procurement of spare parts for that type of car. Based on the Lift Ratio Test that has been carried out, there are two very strong and valid rules to be used in the prediction of BMW auto parts, namely the BMW 320 and BMW 7 SERIES.
MAKING OF WEB-BASED INFORMATION MEDIA FOR CULINARY MEDAN AS A MEANS OF PROMOTION USING UCD (USER CENTER DESIGN) METHOD Ridho Teguh Sanjaya; Marnis Nasution; Syaiful Zuhri Harahap
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 (883.744 KB)

Abstract

Culinary is a part of life that is closely related to daily food consumption. Culinary is a lifestyle that cannot be separated from everyday life. Because everyone needs food that is needed daily. Starting from simple food to high-class and luxurious food Promotion is a communication technique that is used or delivered by using media such as press, television, radio, signboards, posters, and others whose aim is to attract consumer interest in the production of a product. company. Promotion as a medium to bridge the interests of producers with consumers. UCD (User-Centered Design) is a new paradigm in the development of web-based systems. User-centered design (User-Centered Design = UCD) is a term used to describe a design philosophy. The concept of UCD is that the user is at the center of the system development process, and the objectives of the nature, context, and environment of the system are all based on the user experience. PHP is a server-side programming language that is widely used today, especially for creating dynamic websites. For certain things in web development, the PHP programming language is needed, for example to process data sent by web visitors.
COMBINATION OF ACO AND PSO TO MINIMIZE MAKESPAN IN ORDERED FLOWSHOP SCHEDULING PROBLEMS Sastra Wandi Nduru; Ronsen Purba; Andri
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 (1032.489 KB)

Abstract

The problem of scheduling flowshop production is one of the most versatile problems and is often encountered in many industries. Effective scheduling is important because it has a significant impact on reducing costs and increasing productivity. However, solving the ordered flowshop scheduling problem with the aim of minimizing makespan requires a difficult computation known as NP-hard. This research will contribute to the application of combination ACO and PSO to minimize makespan in the ordered flowshop scheduling problem. The performance of the proposed scheduling algorithm is evaluated by testing the data set of 600 ordered flowshop scheduling problems with various combinations of job and machine size combinations. The test results show that the ACO-PSO algorithm is able to provide a better scheduling solution for the scheduling group with small dimensions, namely 76 instances from a total of 600 inctances and is not good at obtaining makespan in the scheduling group with large dimensions. The ACO-PSO algorithm uses execution time which increases as the dimension size (multiple jobs and many machines) increases in a scheduled instance
EXPERT SYSTEM APPLICATION TO DIAGNOSE ESCHERICHIA COLI (E-COLI) BACTERIA IN REFILLED DRINKING WATER USING THE CERTAINTY FACTOR METHOD Rizky Fauziah
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 (454.988 KB)

Abstract

Sometimes many people do not know whether the water is suitable for consumption or not. The reason is because the water that is consumed daily without going through the cooking or boiling process first.Many of the depots that have sprung up today do not include a letter from the local health office stating that the drinking water sold is fit for consumption. Expensive costs and very difficult affairs make the owners of drinking water depots ignore the most important things that actually must be owned. One of the things that can threaten health through drinking water is the presence of Escherichia Coli (E-Coli) bacteria. To find out whether the drinking water that is consumed contains E-Coli bacteria is not easy, because its size is very small and invisible to the eye. One of the consequences that can be caused by E-Coli bacteria is abdominal pain, vomiting, diarrhea, high blood pressure, and even kidney disorders. Certainty Factor (certainty factor) expresses belief in an event or fact based on evidence or expert judgment. Certainty Factor uses a value to assume the degree of confidence of an expert on a data. Many studies get references to do further research with different problems. Where the certainty factor method solves a problem with the concept of belief and disbelief. So that it can be seen whether the certainty factor method can also be used in solving other problems. Where the certainty factor method solves a problem with the concept of belief and disbelief. So that it can be seen whether the certainty factor method can also be used in solving other problems. Where the certainty factor method solves a problem with the concept of belief and disbelief. So that it can be seen whether the certainty factor method can also be used in solving other problems.
COMBINATION OF LOGISTIC REGRESSION AND SVM ALGORITHM WITH HYBRID PSO AND GA BASED SELECTION FEATURE IN CORONARY HEART DISEASE CLASSIFICATION Sutrisno Situmorang; Pahala Sirait; Andri
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 (324.968 KB)

Abstract

The world's high death rate from heart disease requires early prevention by medical doctors to diagnose heart disease early. The machine learning approach makes it possible to predict the risk of developing heart disease by examining certain values at a low cost. This study will contribute to the development of a combination of Logistic Regression and SVM models that integrate SVM and Logistic Regression algorithms by implementing selection features using hybrid PSO and GA methods. The combination concept of Logistic Regression SVM (LRSVM) applied to this study is to reduce the risk of SVM output errors by interpreting and modifying the output of SVM classifiers by the results of Logistic Regression analysis. The test results showed that LRSVM with pso-GA hybrid-based selection feature achieved better performance for coronary heart disease classification with 99.66% accuracy compared to classification accuracy with SVM algorithm without selection feature
KNN METHOD ON CREDIT RISK CLASSIFICATION WITH BINARY PARTICLE SWARM OPTIMIZATION BASED FEATURE SELECTION Harmoko Lubis; Pahala Sirait; Arwin Halim
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 (1044.667 KB)

Abstract

Today, classification performance has become increasingly important for credit risk assessment for loss control and revenue maximization. Therefore, a classification method is required that can accurately and efficiently measure the credit risk level of prospective borrowers as the key to the credit approval process. This study contributes to the development of feature selection methods with SI algorithms that use binary representation, namely feature selection using PSO algorithms with binary representation or Binary Particle Swarm Optimization (BPSO) applied to credit risk classification, with classification evaluation using kNN classification method. The application of feature selection is done to eliminate excessive features, thus reducing the number of features, improving the accuracy of the model, and reducing running time. The test results showed that KNN's best accuracy of 76.40%, can be improved by bpso-based selection feature with better accuracy of 88.70%, with an accuracy improvement of 13.35%. This test showed that bpso-based selection feature technique successfully improved the accuracy of KNN classification on credit risk classification.
FACE IMAGE RETRIEVAL SYSTEM USING COMBINATION METHOD OF SELF ORGANIZING MAP AND NORMALIZED CROSS CORRELATION Amir Saleh; Diky Suryandy; Jesron Nainggolan
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 (438.05 KB)

Abstract

Content based image retrieval (CBIR) is one method in computer vision that is widely applied in various fields of life. In this study, two algorithms will be combined, namely self organizing map (SOM) and normalized cross correlation (NCC) to test the method in the face image retrieval system. The SOM algorithm is used to perform learning on the system created and the NCC method is used to calculate the proximity value between the input image and the image contained in the database to be displayed as the result of image retrieval. The test results in the proposed research show good results with an accuracy rate of face image retrieval of 93.62%. This percentage is higher than using the usual SOM method with an accuracy rate of face image retrieval of 91.62%.

Page 5 of 62 | Total Record : 615

 3   4   5   6   7 

Filter by Year

2018 2023


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