Welcome to IKU Academic Digital Archive System
OpenAccess@IKU is Istanbul Kultur University's Academic Digital Archive System, established in June 2014 to digitally store and provide open access to academic and artistic outputs in line with international standards and intellectual property rights. The system includes various outputs such as articles, presentations, theses, books, book chapters, reports, encyclopedias, and works of art produced by the university's faculty members and students.
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Recent Submissions
Market Basket Analysis Using Apriori and Eclat Algorithm in an E-Commerce Company
(Springer Science and Business Media Deutschland GmbH, 2025) Çatkın, Mehmet; Yüksel, Şengül; Konyalıoğlu, Aziz Kemal; APAYDIN, TUĞÇE; Özcan, Tuncay
E-commerce companies are facing significant challenges due to escalating competition, the homogenization of products and services, rapid shifts in customer demands, and the burgeoning volume of customer transactions. Consequently, these companies grapple with complex problems such as customer segmentation, customer churn analysis, market basket analysis, and the design of product recommendation systems. Leveraging data mining and machine learning algorithms offers substantial opportunities to effectively address these issues. For e-commerce enterprises, analysing customers’ purchasing behaviours and crafting personalized product recommendations not only enhances customer loyalty but also encourages impulse purchases. This approach also contributes to a more user-friendly platform, thereby increasing customer satisfaction. The present study aims to conduct a market basket analysis utilizing real-world data from an e-commerce company. Association rule mining algorithms, specifically Apriori and Eclat, are employed for this analysis. Through these methods, correlations and patterns between product categories are uncovered. Moreover, each algorithm is analyzed by comparing its execution duration and the quality of its results. These specified techniques, including Apriori, an intelligent join-based algorithm, and Eclat, a sophisticated tree-based algorithm, demonstrate remarkable intelligence by efficiently identifying and analyzing patterns within complex datasets. Their innovative methodologies enable them to dynamically adapt to data structures and extract frequent itemset with high performance, as evidenced by their outstanding results in current literature.
On Digamma Series Convertible Into Hypergeometric Series
(American Mathematical Society, 2025) ÇETİNKAYA, ASENA; Karp, Dmitrii
Series containing the digamma function arise when calculating parametric derivatives of hypergeometric functions, and play a role in evaluation of Feynman diagrams. As these series are typically non-hypergeometric, a few instances when they are summable in terms of hypergeometric functions are of importance. In this paper, by employing appropriate limiting processes, we convert multi-term identities for the generalized hypergeometric functions evaluated at positive/negative unity into identities connecting them to digamma series. The resulting formulas can be viewed as hypergeometric expressions for the sum of the partial derivatives of the generalized hypergeometric function with respect to all its parameters, and seem to have no direct analogues in the literature.
Endocrine Disruptors Attitude Scale: A Scale Development Study
(AVES, 2025) MİRAL, MUKADDES TURAN; Mamuk, Rojjin; Di̇şsi̇z, Melike; İşgüven, Şükriye Pınar
Objective: Endocrine disruptors are substances and mixtures that cause health problems in individuals and generations by affecting the endocrine system. There is no measurement tool for the assessment of people’s attitudes toward endocrine disruptors. The development of a valid and reliable measurement tool for the measurement of the attitudes of adult individuals toward endocrine disruptors is the aim of this study. Methods: This study with a methodological design was conducted with 366 participants who were at least 18 years old and literate in Turkish between December 01, 2021, and March 01, 2022, in İstanbul and Famagusta. To collect data, the “Participant Introduction Form” and “Endocrine Disruptors Attitude Scale” were used. Data were evaluated with descriptive statistics, exploratory and confirmatory factor analysis, dependent samples t-test, Cronbach’s α internal consistency coefficient, and Pearson correlation analysis. Results: When the item–total score correlations of 35 items in the draft scale were examined, 14 items with less than 0.30 and negative values were excluded from the scale. The correlation coefficient of all the remaining items was positive and significant (P < .001). The difference between test and retest mean scores was not statistically significant (P > .05). Cronbach’s α reliability coefficient was determined as α = 0.81 for the Consumer behavior sub-dimension, α = 0.80 for Nutrition and hygiene, and α = 0.85 for the whole scale. Conclusion: The scale is concluded to be a reliable and valid tool and can be utilized for determining the determination of attitudes of adults toward endocrine disruptors.
Harmonic Close-to-Convex Mappings Associated with Salagean q-differential Operator
(Babes-Bolyai University, 2025) Mishra, Omendra; ÇETİNKAYA, ASENA; Sokol, Janusz
In this paper, we define a new subclass (Formula presented) of analytic functions and a new subclass (Formula presented) of harmonic functions (Formula presented) associated with Sălăgean q-differential operator. We prove that a harmonic function (Formula presented) belongs to the class (Formula presented) if and only if the analytic functions h+∊g belong to (Formula presented) for each ∊ (|∊| = 1), and using a method by Clunie and Sheil-Small, we determine a sufficient condition for the class (Formula presented) to be close-to-convex. We provide sharp coefficient estimates, sufficient coefficient condition, and convolution properties for such functions classes. We also determine several conditions of partial sums of (Formula presented).
A Bibliometric Analysis of Turkish Educational Sciences in the Context of Education and Science Journal
(Ozgen Korkmaz, 2025) MUHARREM, ALTUNIŞIK; Aktürk, Ahmet Oğuz
This study aims to provide a bibliometric overview of the publication and citation trends of the Education and Science Journal (ESJ), one of the most prestigious and longstanding international journals in the field of educational sciences in Türkiye, which has been in publication for 48 years since 1976. The study covers the period from 2007, when ESJ began to be indexed by Web of Science (WoS), to the present day, and it aims to provide researchers with insights and understanding specific to the journal regarding the current status and development of the field of educational sciences in Türkiye. Metadata for a total of 1270 articles published in the journal during this period were obtained from the WoS database. The study includes bibliometric analyses such as the total number of publications and citations, h-index, citations per paper, average number of citations per year, citation thresholds, and total link strength for ESJ between 2007 and 2022. In addition, the study presents visual maps that are generated on the basis of bibliometric mapping analysis conducted using VOSviewer software, including co-authorship, and co-occurrence of author keywords analyses. The results indicate that ESJ has significantly developed over time, enjoys a significant national authorship network, and that in recent years, researchers publishing in ESJ have been focusing on research topics such as action research, mixed methods, meta-analysis, middle school students, social sciences, and mathematical literacy.