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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 842 Documents
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Edge Detection To Detect Broken Bone On X-Ray Images Using Kirsch Method Mhd Furqan; Rakhmat Kurniawan; Abdul Halim Hasugian; Reza Muhammad
INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Bone is the most important part of the human body and not a few people who have broken bones caused by accidents, neglect and because of age. One of the methods used to identify broken bones is to read the x-ray images manually. Manual checking takes longer and allows mistakes in making decisions when doing a manual check. What's more in reading an x-ray image requires a strong background light (as lighting) to make objects in the X-ray image appear clearer, so we need a method that can facilitate the orthopedic doctor in identifying broken bones. The method proposed in this study is edge detection using the kirsch method. Edge detection aims to improve the appearance of margins, boundaries or objects in the image. The Kirsch method will detect the edges of the eight cardinal directions, namely east, northeast, north, west, northwest, southwest, south and southeast, by convoluting the image using eight kernels. From the results of testing with these methods each cardinal direction has different results. In this study the best results from the eight cardinal directions are the southeast.
IMPLEMENTATION OF SINGULAR VALUE DECOMPOSITION FOR ADDING WATERMARK ON TEXT DOCUMENTS Sinar Sinurat; Edward R Siagian; Pilipus Tarigan
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Watermark is a part of steganography that is used by many users in electronic and non-electronic documents. Watermark certainly does not guarantee the safe use or modification of the document, but only the legitimacy of ownership of the document. Watermarking is a part of steganography that is used by many users in electronic and non-electronic documents. Watermarking certainly does not guarantee the safe use or modification of the document, but only the legitimacy of ownership of the document. Establishing a digital watermark will improve the owner's document security. Hiding a label by inserting datum bits in the image segment using Singular Value Decomposition (SVD), as a part of Watermarking. Watermark domains are digital documents in the form of videos, images, text, sound. Watermarking applications built by applying singular value decomposition to numbers
Data mining using a support vector machine, decision tree, logistic regression and random forest for pneumonia prediction and classification Bahtiar Imran; Zaeniah; Sriasih Sriasih; Surni Erniwati; Salman Salman
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

This study uses Data Mining with four classification models. The object of this research is pneumonia data. The proposed models are Support Vector Machine (SVM), Decision Tree, Logistic Regression and Random Forest. Tests have been carried out using Cross-Validation Sampling and Stratified Sampling using several Folds of 3, 10 and 20. The results obtained are Logistic Regression models get the highest and most consistent accuracy results compared to SVM, Decision Tree and Random Forest. The tests evidence this carried out with the results of Number of Folds 3 getting the AUC value of 0.990, Accuracy 0.962, F1 0.962, Precision 0.962 and Recall 0.962. Number of Folds 10 gets the AUC value of 0.991, Accuracy 0.961, F1 0.961, Precision 0.961 and Recall 0.961. Number of Folds 20 gets AUC 0.991, Accuracy 0.965, F1 0.965, Precision 0.965 and Recall 0.965. From this study, Logistic Regression got good results for predicting and classifying pneumonia.
EMPLOYEE POSITION MUTATIONS DECISION SUPPORT SYSTEM WITH AHP AND SAW METHODS Mahdianta Pandia; Berti Sari Br Sembiring; Friendly Friendly; Zakaria Sembiring
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Employees are important assets for every company, because they greatly influence many aspects of determining the success of the company's work. A company will be able to carry out all its business processes properly 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. From the results of the study it can be concluded, among others: The application of a decision support system that is 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 100%.
DECISION SUPPORT SYSTEM FOR PROVIDING WORK ALLOWANCES AND PUNISHMENTS TO EMPLOYEES USING THE AHP AND SMART METHOD Berti Sari Br Sembiring; Mahdianta Pandia; Fransisca Br Sebayang; Harianta Sembiring
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

From the results of the study it can be concluded, among others: The decision support system that was built was very helpful to speed up data processing in decision making for the provision of work benefits and punishments to employees. The SMART method is a suitable method to be applied in decision making by sharing alternatives, especially determining the provision of work benefits and punishments to employees quickly and precisely. The level of accuracy of the test results using the SMART method is 100%. The decision support system application that is built is dynamic in terms of determining criteria and weighting. So, it can be changed according to the needs of the company in providing work benefits and punishments
Analysis of Higher Education Academic Service Satisfaction Levels using the Service Quality and Importance-Performance Analysis methods Beny Irawan
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

The academic services of the college today have undergone very significant changes in a very fast time. For these changes, and evaluation of academic services is carried out by measuring the performance of the services provided. To obtain the level of satisfaction, the Service Quality (Servqual) method is used, and to obtain performance from the attributes of the questionnaire to improve its performance, the Importance-Performance Analysis (IPA) method is used. The results of the analysis and data processing using the servqual method at gap 5 showed the gap score gap of each variable so that the Guarantee variable with a score of -0.27, Reliability -0.31, Empathy -0.34, Date Power -0.42 and Tangibles with a score of -0.49. Overall the gap score is -0.37. This shows that any level of service satisfaction expected by students for academic services has not met expectations, as well as the variables of the servqual method. To determine the proposed service improvement based on the attributes of the questionnaire using the Importance-Performance Analysis (IPA) method, 8 attributes are in quadrant I that need to be prioritized for improvement. The attributes are attribute number 4 with a respondent suitability rate of 84.70%, attribute number 5 with a respondent suitability rate of 85.90%, attribute number 10 with a respondent suitability rate of 88.59%, attribute number 15 with a respondent suitability rate of 89.88%, attribute number 16 with a respondent suitability rate of 87.62%, attribute number 17 with a respondent suitability rate of 90.14%, attribute number 18 with a respondent conformity rate of 89.22% and attribute number 27 with a respondent conformity rate of 88.87%.
Analysis of Elearning Quality Measurement with Webqual method using Artificial Neural Networks Erwin Daniel Sitanggang; Misdem Sembiring; Anjar Pinem; Maranata Pasaribu
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Currently, artificial intelligence is a concern for the world because of its increasingly rapid and sophisticated application in helping humans to complete their work in everyday life. One of the widely used methods is artificial neural networks that are part of deep learning and a subsection of machine learning. In its network training, the data used as input is the gap score of each webqual dimension and the data used as the output is the gap score of the average webqual attributes of each respondent. The training process is expected to produce an actual output close to the predetermined target output, resulting in the best model of artificial neural networks with feedforward backpropagation algorithms. From the results of the training experiment, the best model of artificial neural network architecture was obtained with a feedforward backpropagation algorithm at the time of training from 174 data to be able to replace the Webqual method in this study using the 3-20-1 model and the algorithm used was Levenberg-Marquardt (trainln). Where there is 1 Input layer with 3 neuron units, 1 hidden layer with 20 neuron units and 1 Output layer with 1 neuron unit with a mean square error (mse) of 0.00000000000721 and regression of 1 or 100%. And after testing using 58 data using the network configuration obtained during training, the results of the comparison between the network output and the target were 100% accurate.
Application of Data Mining in the Best Classification of Animal Feed Types Purwa Hasan Putra
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

The company's goal is to produce high quality aquaculture products such as feed, seeds, pet feed, probiotics to shrimp products and processed food for the domestic and export markets. The company is still experiencing difficulties in determining the appropriate composition for the manufacture of animal feed. So that the animal feed produced has poor quality. Therefore, we need a decision support system that can assist in the process of determining the composition in the manufacture of animal feed. Because Data Mining is a computer-based system capable of solving unstructured problems. To be able to assist in the process of determining the composition of the company's animal feed, the author uses the Multi Factor Evaluation Process method. The Multi Factor Evaluation Process method is a method that breaks up a complex, unstructured situation into its component parts, the Multi Factor Evaluation Process method is a specification of the problem, in which decision makers must evaluate each alternative with multiple specific criteria. From the results of the study, it can be concluded, among others: The company must provide supporting equipment to run the application of the MFEP Method in Determining the Composition of this Feed so that it runs as desired. To achieve the purpose of the application of the MFEP Method Application in Determining the Composition of Animal Feed that is designed, it is hoped that this research can continue so that the system can be based on Client-Server and Online.
Applications Based on Expert Systems For Early Diagnosing Anemia in Pregnant Women Meizar Abdul; Nur Hayati; Utami Utami
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Anemia in pregnant women is commonly called iron deficiency anemia with hemoglobin levels in red blood cells 10.0 grams/100 milliliters (10 grams/deciliter). This type of anemia is prone to be experienced by pregnant women because pregnant women must require very high oxygen levels. This type of anemia is not so dangerous but can be dangerous if there are congenital abnormalities of the body. Therefore, the authors feel it is important to identify this type of anemia early because there is a dangerous potential. The author makes an application based on an expert system that early diagnoses a pregnant woman with iron deficiency anemia or not. The method used is Bayes' theorem. The results obtained are efficiency and speed in early diagnosis of anemia in pregnant women used in hospitals. Coal Inalum. With a situation where the hospital only has one doctor serving many pregnant women patients. With the application of an expert system for early diagnosis of anemia in pregnant women, it can help users (doctors) in knowing the early symptoms of whether a pregnant woman has iron deficiency anemia or not.
Document Based Text Data Security Using the Prime Generator Algorithm Fermat's and the ElGamal Algorithm Andre Gusli Agus Riadi; Mhd.Furqan; Rakhmat Kurniawan
INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Elgamal is an asymmetric key cryptography algorithm, which means that Elgamal cryptography requires two keys to perform the encryption and description processes, while the key used in the Elgamal algorithm is the public key for encryption while the private key is for decryption. The public key and private key are obtained using the help of other algorithms, one of which is the fermat prime generator algorithm, this fermat prime generator algorithm has a role to find prime random numbers where the randomized prime numbers obtained are used to form the public and private keys. In this study, the researcher wants to combine these two algorithms to secure text-based document files. The result of this research is an application that can secure text-based document files.

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