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Copyright of Acta Infologica is the property of Acta Infologica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, it was aimed to determine the important variables that can predict the success of reading comprehension with 34 independent variables obtained from the student questionnaire given to the students who participated in PISA in 2018. For this purpose, 79 countries participating in PISA were put in order of success percentage. Then, with equal slices, countries were divided into lower, middle and upper slices. The study sample was created by selecting 9 countries including Turkey according to their percentiles. In the analyzes made with the logistic model using Turkey, low, medium, high achievement group and study sample data, the important variables predicting reading comprehension success varied between 5 and 8. According to the results obtained, for Turkey, low, middle and high achievement group countries and study sample, it is determined that the important common predictors of success are, the difficulty perception of the PISA test, the highest education level index of the parents and the educational items in the house. Then, classification, cross-validation and prediction performances of success with important variables were calculated. It has been observed that with the estimations made with important variables, results were close to the performances of the models obtained with 34 variables. [ABSTRACT FROM AUTHOR]

The aim of this study is to determine the fraud risk of the independently audited financial statements of companies whose stocks are traded in the Borsa Istanbul Textile, Clothing and Leather sector between 2015-2019 using data mining-based methods, through financial ratios, and accordingly, to reveal the success of these methods in detecting fraud. For this purpose, independent audit reports and weekly Capital Market Boards of Turkey (CMB) Bulletins were examined within the scope of the study, and cases of applying to fraudulent financial reporting practices were determined. In this context, 127 financial statements and independent audit reports of relevant periods were examined. In the study, 12 financial ratios used in literature to explain fraudulent financial reporting and 10 methods based on data mining were used. According to research findings, all models based on data mining used within the scope of the study were more than 70% successful in correctly classifying financial statements that are considered to have fraud risk and financial statements that are considered to have no fraud risk, and the most successful methods are models established with J48 and Deep Learning methods. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Higher Education / Yüksekögretim Dergisi is the property of Deomed Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Financial Politic & Economic Reviews / Finans Politik & Ekonomik Yorumlar is the property of Journal of Financial Politic & Economic Reviews / Finans Politik & Ekomomik Yorumlar and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: In this study, it is aimed to provide a dynamic structure to the summary status and analysis results based on the current COVID-19 data of the countries based on changing status of global COVID-19 outbreak in the world and in Turkey; thus, to support fast and proactive decisions. In this scope, to define COVID-19 based on data, an online R-Shiny application is developed (https://elifkartal.shinyapps.io/covid19/). Material and Method: In this study, CRoss-Industry Standard Process for Data Mining - CRISP-DM is used as the study method. The changing situation of COVID-19 in global and national dimensions was evaluated. New variables are calculated such as Linear Change Rate (LCR), Exponential Growth Coefficient (EGC), and required days to double cases. Cluster analysis was performed by applying the k-Means data mining algorithm to the data reinforced with the new variables and similarities of countries were determined. The countries closest to the cluster average are accepted as cluster centers and the countries in the same cluster are ranked according to their distance from the cluster center. Results: One of the most important findings of the study is that the trends of LCR and EGC are the same. As such, it can be said that COVID-19 does not display an exponential behavior or can be controlled. With the developed application, the countries in which the cluster is located, regardless of their geographical location and dynamically according to time, the possible risk situations and similarities of the countries in the same cluster have been determined more precisely. Conclusion: With this study and the application developed; depending on changing status of global COVID-19 outbreak in the world and in Turkey, a dynamic structure has been given to the summary status and analysis results based on the current COVID-19 data of the countries, thus, it has been provided to support fast and proactive decisions. [ABSTRACT FROM AUTHOR]

Copyright of Optimum: Journal of Economics & Management Sciences / Ekonomi ve Yönetim Bilimleri Dergisi is the property of Optimum: Journal of Economics & Management Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of International Journal of Economic & Social Research is the property of Abant Izzet Baysal University, Faculty of Economics & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The repeating agendas in the published news stories about the organizations build the identity of these organizations. A particular agenda may emerge as a natural result of the activities of the organization, but also as the results of this organization's own public relations efforts. The other side that shapes this agenda is the media. The choice of topic by the media organization and the way the topics are evaluated are the most important factors determining how the agenda is to be perceived. In this case, the transformation from pure reality to the to news is the special process. form a special process. This process is of interest to the agenda-setting theory. This theory deals with the relations between media, society, and reality. In this study, the news about the Agriculture and Rural Development Support Agency (ARDSI) of Turkey. This institution is a payment agent for the European Union agricultural funds for Turkey. Within the scope of the study, 396 news scraped from 4 different news sources were analyzed by the method called text mining. As a result, it is seen that the agenda of the news are: new enterprises established with the grants distributed by the institution and the meetings and training realized by the institution. Moreover, it was found that the agenda of the news stories and the legal functions of the institution are similar. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Administrative Sciences / Yonetim Bilimleri Dergisi is the property of Canakkale Onsekiz Mart Universitesi, Terzioglu Kampusu and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Faculty of Educational Sciences is the property of Ankara University, Faculty of Educational Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Dokuz Eylul University Muhendislik Faculty of Engineering Journal of Science & Engineering / Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi is the property of Dokuz Eylul Universitesi Muhendislik Fakultesi Fen ve Muhendislik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Karaelmas Science & Engineering Journal / Karaelmas Fen ve Mühendislik Dergisi is the property of Karaelmas Science & Engineering Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Finance Letters / Maliye Finans Yazıları Dergisi is the property of Maliye Finans Yazilari Yayimcilik Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Data Mining is used to describe the totality of techniques which aim to find the unexplored patterns in a set of data. The purpose of data mining is to create models of decision-making devoted to estimations of future behavior based on analysis of past activities. In this study the shopping data of the customers of an authorized service, operating in the automative sector in Turkey, were analyzed using Apriori and FPGrowth Algorithms. This way, it is observed which products were purchased together by customers and in line with this observation, campaigns and promotions were given a direction to increase the profit. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Finance Letters / Maliye Finans Yazıları Dergisi is the property of Maliye Finans Yazilari Yayimcilik Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Data mining methods have been successfully applied to different fields. Aviation industry is one of these fields. There is a large amount of knowledge and data accumulation in aviation industry. These data could be stored in the form of pilot reports, maintenance reports, incident reports, component reports or delay reports. This paper explains the data mining application on the component reports of an airline company in Turkey. In this study, we applied data mining functions on the component reports. The purpose of our application is to find out a rule about the warning level of the components to do correcting operation before any fault. As a result we found out a meaningful rule that presents the formulation of the warning level of the components. The rules found are tested in terms of their accuracy and reliability. [ABSTRACT FROM AUTHOR]

Copyright of Iş, Güç: The Journal of Industrial Relations & Human Resources is the property of Is, Guc: The Journal of Industrial Relations & Human Resources and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)