Walfaanaa M Ejeta

Addis Ababa University, Computational Science, Graduate Student

Followers

Following

Public Views

My name is Walfaanaa Magarsaa Ejeta I was, born in 1990 in Ginchi, Oromia, Ethiopia, I am a highly accomplished professional in the field of Data Science. I have dedicated my career to acquiring extensive knowledge and expertise in statistical analysis, business administration, and computational data science. In 2016, I completed my Bachelor of Science degree in Statistics from Ambo University, where I gained a solid foundation in statistical methods and data analysis. Eager to enhance my understanding of business principles, I pursued a Master of Business Administration (MBA) degree at Rift Valley University, which I successfully obtained in 2020. This additional qualification equipped me with the necessary skills to apply my statistical expertise within a business context. Driven by my passion for exploring the vast potential of data-driven technologies, I embarked on a Master of Science (MSc) program in Computational Data Science at Addis Ababa University in 2024. Throughout this program, I have honed my advanced data analysis, machine learning, and predictive modeling abilities. Since 2017, I have been gainfully employed, utilizing my exceptional skills and expertise in Data Science. I have consistently demonstrated my proficiency, earning the status of a professional expert in Data Science. My extensive knowledge and experience have allowed me to contribute significantly to my organization's data-driven decision-making processes, enabling them to make informed strategic choices based on accurate analysis and insights. My unwavering commitment to expanding my expertise in the dynamic field of Data Science, as evidenced by my educational achievements and professional accomplishments, positions me as a valuable asset within the industry. With my comprehensive skill set and dedication to advancing the field, I continue to make a meaningful impact in data-driven decision-making and analytics.
Supervisors: Moti Tafa and Natei Ermias Benti
Phone: +251917089988
Address: Addis Ababa,Ethiopia
Addis Ababa

less

Interests

Uploads

Papers by Walfaanaa M Ejeta

Artificial Intelligence-Enhanced Credit Risk Assessment on Commercial Bank of Ethiopia

Thesis, 2024

Accurately identifying credit risk is essential for the successful operation and growth of any bu... more Accurately identifying credit risk is essential for the successful operation and growth of any business. By accurately predicting an applicant's loan status, businesses can better understand the drivers of credit risk and develop informed market strategies to promote business expansion. The goal of this research is to develop a machine learning model that can reliably predict the loan status (approved or rejected) of applicants to the Commercial Bank of Ethiopia (CBE). The study utilized a dataset of 32,285 applicants with 10 attributes. To evaluate the performance of different classifiers, the overall accuracy was used as the primary metric. Supervised machine learning techniques including Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Deep Neural Network (DNN) were applied to the applicant loan status prediction task, based on their widespread use in prior literature. Feature importance and correlation matrix analysis were used for feature selection. Additionally, the SMOTE technique was employed to balance the dataset. The results show that the RF classifier achieved the best overall performance, with an accuracy of 93.62%, a recall of 94.72%,

Download

College of Natural and Computational Sciences Computational Data Science program Artificial Intelligence-Enhanced Credit Risk Assessment on Commercial Bank of Ethiopia

Download

Walfaanaa magarsaa (final thesis123) (3)1 (3)

Download

THE IMPACT OF ICT ADOPTION ON STUDENT `S ACADEMIC PERFORMANCE IN HIGHER EDUCATION INSTITUTION: THE CASE OF RIFT VALLEY, BURAYU

Academic research, 2020

This study will investigate and explore the adoption of information communication technology in t... more This study will investigate and explore the adoption of information communication technology in the higher education sector and its impact on students' academic performance. The main objective of this study was to examine the moderators’ effect on internet service, research, and development, students’ motivation, and Technology advancement on the relationship between ICT adoption and academic achievement. By using both quantitative and qualitative research approaches and a sample size of 302 respondents’ would be selected from different departments to describe the ICT adoption in higher education institutions and the relative performance of students belonging to three different levels of education programs in Rift Valley universities at the Buraus campus. Structure equation modeling was chosen to determine the validity of the research model. The Analysis of Moment Structures (AMOS), especially would be used for structural equation modeling, and path analysis is used as a research tool. The findings reveal that there existed a relationship between ICT adoption and academic performance in a conservative environment. A discussion of findings, limitations, and suggestions for future research would be provided in the study. Finally, it also provided implications of the current study to the existing knowledge.
Keywords: Availability of internet, research, and development, motivation and technology advanced

Download

Artificial Intelligence-Enhanced Credit Risk Assessment on Commercial Bank of Ethiopia

Thesis, 2024

Download

College of Natural and Computational Sciences Computational Data Science program Artificial Intelligence-Enhanced Credit Risk Assessment on Commercial Bank of Ethiopia

Download

Walfaanaa magarsaa (final thesis123) (3)1 (3)

Download

THE IMPACT OF ICT ADOPTION ON STUDENT `S ACADEMIC PERFORMANCE IN HIGHER EDUCATION INSTITUTION: THE CASE OF RIFT VALLEY, BURAYU

Academic research, 2020

Download

Walfaanaa M Ejeta

Uploads

Papers by Walfaanaa M Ejeta

Log In