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Alde Alanda
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International Journal of Advanced Science Computing and Engineering
Published by Society of Visual Informatics
ISSN : 27147533     EISSN : 27147533     DOI : https://doi.org/10.30630/ijasce
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
The journal scopes include (but not limited to) the followings: Computer Science : Artificial Intelligence, Data Mining, Database, Data Warehouse, Big Data, Machine Learning, Operating System, Algorithm Computer Engineering : Computer Architecture, Computer Network, Computer Security, Embedded system, Coud Computing, Internet of Thing, Robotics, Computer Hardware Information Technology : Information System, Internet & Mobile Computing, Geographical Information System Visualization : Virtual Reality, Augmented Reality, Multimedia, Computer Vision, Computer Graphics, Pattern & Speech Recognition, image processing Social Informatics: ICT interaction with society, ICT application in social science, ICT as a social research tool, ICT education
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 4 Documents
 1 
Search results for , issue "Vol. 2 No. 3 (2020)" : 4 Documents clear
An Information Entropy Based to Identify Dominant Species for No Biological Data Genes Nazirah, Nurul Ain; Kasim, Shahreen; Meidelfi, Dwiny
International Journal of Advanced Science Computing and Engineering Vol. 2 No. 3 (2020)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1167.907 KB) | DOI: 10.62527/ijasce.2.3.101

Abstract

This report discusses about the dominant species of no biological data genes. This genes are belong to animal species. Gene is one of a process where the biological data encoded in the gene that instructed by the DNA to convert into a functional product such as protein. In gene classification, with the growth of using gene expression database, there are not enough tools to extract the gene expression from these databases. There exist over 23,000 to 50,000 genes for animal genome. So, this might contribute to data redundancy as problems can happen while handling a huge database. Therefore, to overcome the problem, many approaches to cluster and determine the dominant species have been proposed in the previous literature. For this project, in order to determine the dominant species, the information entropy based method is used. As conclusion, the purpose of this research is to identify the dominant species of no biological genes using entropy method proposed.
Application For Petty Cash Management Norung, Muhammad Hazim Muhamad; Kasim, Shahreen; Defni, -
International Journal of Advanced Science Computing and Engineering Vol. 2 No. 3 (2020)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (598.73 KB) | DOI: 10.62527/ijasce.2.3.102

Abstract

Some people currently face into traps of dept and overspending without even realizing it. The feeling of never having enough cash or living paycheck to paycheck can lead serious final problems that can lead into financial difficulties over a lifetime. This study aims to determine how application can manage the financial problems. Specifically, it manages on how you spend your money and get the overview about it. In this application, it uses financial skills such as budgeting, saving and spending. It refers to the strategies technique to determine the use of an individual. To achieve a better understanding on the money management, a report is created to see the whole month transaction such as saving and spending. The report will show the total amount of money spent and where the money is going. You will understand your expenses with the report and create a budget for future expenses. By having good financial skills, you can have a strategy on how you want to manage your money. Creating and sticking to a budget might seem tough to achieve but it helps us to see full transparency our financial situation.
The Potential of Coir Composite in The Production of Spare Parts and Equipment for Vehicles Transporting Goods by Road and Water Nguyen, Dinh Tuyen; Nguyen, Thi Bich Ngoc
International Journal of Advanced Science Computing and Engineering Vol. 2 No. 3 (2020)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.2.3.107

Abstract

Traditional materials used in the production of industrial equipment parts are now wood and metal. But these materials are gradually scarce, the need to find alternative materials is necessary. On that basis, there have been many studies on fiber reinforced composites in which glass fiber reinforcement is widely applied. However, fiberglass-reinforced composites are difficult to decompose and recycle, leading to serious environmental impacts. To solve this problem, scientists are working to apply bio-fibers to replace glass fibers. In recent years, there have been many studies on coir fiber and its application in the manufacture of coir fiber fortified composites. This article reviews the potential of coir fiber fortified materials applied in the production of industrial products.
Performance Comparison of Apriori, ECLAT and FP-Growth Algorithm for No Biological Data Genes for Association Rule Learning Anuar, Anies Nurfazlin; Kasim, Shahreen; Hendrick, -
International Journal of Advanced Science Computing and Engineering Vol. 2 No. 3 (2020)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.2.3.103

Abstract

This project is carried out to study the performance comparison of Apriori Algorithm, ECLAT Algorithm and FP-Growth Algorithm for no biological data genes. There are many genes with no biological data, but for this project we have chosen 4 types of no biological data genes. No biological data genes are genes that have no specific data about themselves such as location, behaviour and function of the genes. Association Rule Learning is a technique implementing big data in finding frequent item-sets. Frequent item-sets are items that occur frequently in the database. The performance of these three algorithms is compared through time efficiency and the ability to process small and large datasets. After the comparison, we can conclude that FP-Growth algorithm is the fastest algorithm for small data-set and Apriori algorithm and ECLAT algorithm takes lesser time to generate the frequent item-sets compared to FP-Growth algorithm.

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