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JOIV : International Journal on Informatics Visualization
Published by Politeknik Negeri Padang
ISSN : 25499610     EISSN : 25499904     DOI : -
Core Subject : Science,
Computer Science & IT
JOIV : International Journal on Informatics Visualization is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of Computer Science, Computer Engineering, Information Technology and Visualization. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the JOIV follows the open access policy that allows the published articles freely available online without any subscription.
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Articles 13 Documents
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Search results for , issue "Vol 3, No 4 (2019)" : 13 Documents clear
The Use of Data Mining Techniques in Predicting the Noise Emitted By the Trailing Edge of Aerodynamic Objects Abdusalam Shaltooki; Mojtaba Jamshidi
JOIV : International Journal on Informatics Visualization Vol 3, No 4 (2019)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1049.94 KB) | DOI: 10.30630/joiv.3.4.242

Abstract

Aerodynamic is a branch of fluid dynamics that evaluates the behavior of airflow and its interaction with moving objects. The most important application of aerodynamic is in aerospace engineering, designing and construction of flying objects. Reduction of noise emitted by aerodynamic objects is one of the most important challenges in this area and many efforts have been to reduce its negative effects. The prediction of noise emitted from these aerodynamic objects is a low-cost and fast approach that can partially replace the "fabrication and testing" phase. One of the most common and successful tools in prediction procedures is data mining technology. In this paper, the performance of different data mining algorithms such as Random Forest, J48, RBF Network, SVM, MLP, Logistic, and Bagging is evaluated in predicting the amount of noise emitted from aerodynamic objects. The experiments are conducted on a dataset collected by NASA, which is called "Airfoil Self-Noise". The obtained results illustrate that the proposed hybrid model derived from the combination of Random Forest and Bagging algorithms has better performance compared to other methods with an accuracy of 77.6% and mean absolute error of 0.2279.
Unique Model of Criminal Record Management System in the Perspective of Somalia Fowzi Jamal Mohamed Barrow; Mohammad Jahangir Alam; Md. Nurul Mustafa
JOIV : International Journal on Informatics Visualization Vol 3, No 4 (2019)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1382.329 KB) | DOI: 10.30630/joiv.3.4.255

Abstract

The project Criminal Record Management System in the perspective of Somalia is a Criminal record management system that uses to record crime activities of criminals. It can be used to report criminal activities. This project is mainly useful for law and enforcement agencies in Somalia. The law and enforcement authority can preserve records of the criminals and search for any criminal using the system. This is an online web application with a database system in which police will keep the record of criminals who have been arrested.  We have used HTML, JavaScript, CSS, PHP, MySql and Bootstrap to develop this system.  We have also used binary search algorithm to find a criminal from the database. The project's interface is very user-friendly and helpful for authority.
Role of Different Integer Virtual Machine in Cloud Data Center Arif Ullah; Nazri Mohd Nawi; Hairulnizam Bin Mahdin; Samad Baseer; Mustafa Mat Deris
JOIV : International Journal on Informatics Visualization Vol 3, No 4 (2019)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1471.164 KB) | DOI: 10.30630/joiv.3.4.274

Abstract

In modern data centres of cloud computing contains virtualization system. In order to improve network stability, energy efficiency, and makespan proper virtualization need. The virtual machine is one of the examples of virtualizations. Cloud computing data centres consist of millions of virtual machine to manage load balancing. In this study check the different number of virtual machine role in data centres, for that purpose, we established a network with the help of cloudsim and compare different data centres at each zones taking a different number of the virtual machine with different paramater and network banwith.After the simulation the result shows that increasning in the number of VM can affect the netwok accuracy in term of energy ,processing time ,coast and network stabality . 

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