Veri Bilimi Anabilim Dalı Tez Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/220

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Analysis of online marketplace sales prediction based on machine learning algorithms: A case of Turkish e-commerce site
(Abdullah Gül Üniversitesi / Sosyal Bilimler Enstitüsü, 2023) Kaya, Ecem; AGÜ, Sosyal Bilimler Enstitüsü, İşletme ve Ekonomi İçin Veri Bilimi Ana Bilim Dalı
Internet shopping has grown in popularity as more of our daily requirements have begun to be addressed online. Learning about the preferences and motivations of customers in the Turkish market and guiding e-commerce platforms to adapt their marketing strategies and increase customer satisfaction is important for both resource allocation and cost minimization. The purpose of this paper is to estimate future sales for popular e-commerce sites based on behavioral factors such as discounts, price or free shipping. Therefore, real-time and experiment-independent data are collected from the sales made by one of Turkey's most popular e-commerce sites. In order to produce predictions, we employ Artificial Neural Networks, Support Vector Regression, K-Nearest Neighbors Regressor, OLS regression, and Nu-Support Vector Regressor. The models developed using machine learning algorithms attempt to estimate the number of sales based on independent factors such as price, discount rate, and user ratings. As the result of this research, we calculate and compare the accuracy of the models with root mean squared errors and R².
EFFECT OF IMPLEMENTED POLICIES IN TÜRKİYE AND SWEDEN ON EQUAL OPPORTUNITY AND HIGHER EDUCATION OUTCOMES DURING COVID-19 PERIOD
(Abdullah Gül Üniversitesi, Sosyal Bilimler Enstitüsü, 2024) Dalan, Ayşenur; AGÜ, Sosyal Bilimler Enstitüsü, İşletme ve Ekonomi İçin Veri Bilimi Ana Bilim Dalı
This thesis delves into the impact of COVID-19 policies implemented in Türkiye and Sweden on equal opportunity within higher education and explores the consequential higher education outcomes. The research employs a mixed-methods approach, incorporating both qualitative and quantitative methodologies. Through an examination of socio economic structure, education system, the study elucidates the distinctive approaches taken by Türkiye and Sweden. The findings contribute significantly to a comprehensive understanding of global education policy responses during crises, emphasizing the pivotal role of ensuring equal opportunity. By scrutinizing the specific measures undertaken by both countries, this study not only informs the on education policy during extraordinary times but also provides valuable insights for policymakers, educators, and stakeholders seeking to enhance equal opportunity and foster positive outcomes in higher education.
Enhancing grouping-scoring-modeling (G-S-M) approach through a statistical pre-scoring component: A case study for high-dimensional transcriptomic data analysis
(Abdullah Gül Üniversitesi / Sosyal Bilimler Enstitüsü, 2024) KHOKHAR, MAHAM; AGÜ, Sosyal Bilimler Enstitüsü, İşletme ve Ekonomi İçin Veri Bilimi Ana Bilim Dalı
Rapid advancements in transcriptomic technologies have significantly increased the volume of data available for analysis, which presents challenges in terms of efficiency and computational demand. This thesis introduces a Pre-Scoring component to the Grouping-Scoring-Modeling (G-S-M) framework to address inefficiencies caused by the excessive number of gene groups generated by traditional GSM. By selectively prioritizing gene groups based on their statistical significance, this innovation aims to reduce the computational demands associated with scoring these groups using machine learning models, thereby streamlining the analysis process. Assessed across nine diverse Gene Expression datasets, the Pre-Scoring G-S-M framework not only maintained accuracy comparable to the traditional approach but did so with significantly fewer genes. This refinement conserves resources while maintaining the robustness and reliability of the data analysis, crucial for advancing research in personalized medicine and therapeutic strategies. The findings suggest that the modified G-S-M framework serves as a valuable tool in bioinformatics, offering a more efficient approach to handling large-scale genomic datasets. Future work will focus on adapting this enhanced framework to incorporate diverse types of omics knowledge, such as proteomics and metabolomics, further optimizing its performance to broaden its applicability in both clinical and research settings
How does quality of life (QoL) affect city attractiveness and internal migration in Turkey?
(Abdullah Gül Üniversitesi / Sosyal Bilimler Enstitüsü, 2023) Özer, İsmet Selçuk; AGÜ, Sosyal Bilimler Enstitüsü, İşletme ve Ekonomi İçin Veri Bilimi Ana Bilim Dalı
The current study reexamines the link between quality of life (QoL) factors, city attractiveness, and internal migration in Turkey. The management of internal flows can bring significant benefits to a country in balancing the opportunities between regions or cities. To tackle unequal access to opportunities, the factors that induce internal migration should be understood. This study examines a set of pull and push factors for internal migration by spatial econometric analysis and GIS applications. This thesis finds that when the accessibility of amenities increases, the city becomes more attractive and preferable for migrants. In addition, socioeconomic factors also play a significant role in the decision-making process of migrants. In this study, this thesis used a panel dataset that includes socioeconomic and contextual data such as distances to the amenities for each Turkish city in the years between 2012 and 2021. The results show that, in Turkey, internal migration flows from the East to the West, where opportunities are better. Finally, the human capital level of migrants can cause a variety of thoughts about factors, and it can change the order of significance of the variables for people who have a different level of human capital such as education level. Based on the findings, the paper offers several policy suggestions for ensuring a balanced migration in Turkey.

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