Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Journal of Electrical Engineering and Computer (JEECOM)
Ismail, Rasha Rokan
Unknown Affiliation
Control & Systems Engineering Electrical & Electronics Engineering Energy

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Classification of Credit Card Frauds Detection using machine learning techniques Ismail, Rasha Rokan; Khorsheed, Farah Hatem
Journal of Electrical Engineering and Computer (JEECOM) Vol 5, No 2 (2023)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v5i2.6602

Abstract

Credit card fraud refers to the illegal activities carried out by criminals. In this research paper, we delve into the topic by exploring four different approaches to analyze fraud, namely decision trees, logistic regression, support vector machines, and Random Forests. Our proposed technique encompasses four stages: inputting the dataset, balancing the data through sampling, training classifier models, and detecting fraud. To analyze the data, we utilized two methods: forward stepwise logistic regression analysis (LR) and decision tree analysis (DT), in addition to Random Forest and support vector machine. Based on the outcomes of our analysis, the decision tree algorithm produced the highest AUC and accuracy value, achieving a perfect score of 1. On the other hand, logistic regression yielded the lowest values of 0.33 and 0.2933 for AUC and accuracy, respectively. Moreover, the implementation of forest algorithms resulted in an impressive accuracy rate of 99.5%, which signifies a significant advancement in automating the detection of credit card fraud.
Predicting the relative humidity of allergic asthma using GA Ismail, Rasha Rokan
Journal of Electrical Engineering and Computer (JEECOM) Vol 6, No 2 (2024)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v6i2.8548

Abstract

 Asthma is a serious chronic disease that affects the airways, and the occurrence of this disease depends on many factors, including psychological ones, and others because of specific foods, and others depend on weather conditions such as the ambient temperature and relative humidity of the air. In this research, the disease was diagnosed by identifying one of its causes, which is air humidity, which is an important factor for exacerbation of asthma, using one of the algorithms of artificial intelligence, which is the genetic algorithms, which depend on the symptoms of the disease and the degree of humidity in the air. Examples were extracted from contaminated and also non-infected individuals, and also the formula was related to them as well as the success price was 95%.
Co-Authors Khorsheed, Farah Hatem