Data mining of Students Withdrawal at University of Tehran, Focusing on Fee Paid Students (to prevent customer churn)
Student withdrawal in higher education is one the important challenges in universities. This paper considers the admission of fee paid students as a business and their withdrawals as customer churn. The aim is to investigate the attrition and predicted risk of attrition to adapt interventionist poli...
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| Format: | Article |
| Language: | English |
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University of Tehran
2015-06-01
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| Series: | Journal of Information Technology Management |
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| Online Access: | https://jitm.ut.ac.ir/article_53969_0368dcb86cf8dbb8091a8874402b45be.pdf |
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| author | Saied Ali Akbar Ahmadi Davood Karimzadgan Toraj Khairati Kazerooni |
| author_facet | Saied Ali Akbar Ahmadi Davood Karimzadgan Toraj Khairati Kazerooni |
| author_sort | Saied Ali Akbar Ahmadi |
| collection | DOAJ |
| description | Student withdrawal in higher education is one the important challenges in universities. This paper considers the admission of fee paid students as a business and their withdrawals as customer churn. The aim is to investigate the attrition and predicted risk of attrition to adapt interventionist polices deterrent. This study is a descriptive an applicable technique that uses quantitative and qualitative data. It uses Crisp technology of data mining. The data are derived from educational system of University of Tehran including 21420 fee paid students accepted at 2010 to 2014. The main goal is to analyze the behavior that is at risk of attrition and withdrawal. After data analyze and construction of predictive modeling, the probability table of attrition and regression model will be presented. The final results show that the first and second semester (especially the age range 24-31) of M.Sc students are the most likely risk of withdrawal of happening. |
| format | Article |
| id | doaj-art-1ffd226f883d402e9e7375b7d577dac9 |
| institution | OA Journals |
| issn | 2008-5893 2423-5059 |
| language | English |
| publishDate | 2015-06-01 |
| publisher | University of Tehran |
| record_format | Article |
| series | Journal of Information Technology Management |
| spelling | doaj-art-1ffd226f883d402e9e7375b7d577dac92025-08-20T01:51:06ZengUniversity of TehranJournal of Information Technology Management2008-58932423-50592015-06-017221723810.22059/jitm.2015.5396953969Data mining of Students Withdrawal at University of Tehran, Focusing on Fee Paid Students (to prevent customer churn)Saied Ali Akbar Ahmadi0Davood Karimzadgan1Toraj Khairati Kazerooni2Prof. Faculty of Management , Payam Noor University West Unit, Tehran, IranAssistant Prof. Faculty of Computer Engineering , Payam Noor University, Tehran, IranMSc. Student in Information Technology Management, Faculty of Manegent Payam Noor University of Tehran, IranStudent withdrawal in higher education is one the important challenges in universities. This paper considers the admission of fee paid students as a business and their withdrawals as customer churn. The aim is to investigate the attrition and predicted risk of attrition to adapt interventionist polices deterrent. This study is a descriptive an applicable technique that uses quantitative and qualitative data. It uses Crisp technology of data mining. The data are derived from educational system of University of Tehran including 21420 fee paid students accepted at 2010 to 2014. The main goal is to analyze the behavior that is at risk of attrition and withdrawal. After data analyze and construction of predictive modeling, the probability table of attrition and regression model will be presented. The final results show that the first and second semester (especially the age range 24-31) of M.Sc students are the most likely risk of withdrawal of happening.https://jitm.ut.ac.ir/article_53969_0368dcb86cf8dbb8091a8874402b45be.pdfcustomer churncustomer relation managementeducational data miningwithdrawal |
| spellingShingle | Saied Ali Akbar Ahmadi Davood Karimzadgan Toraj Khairati Kazerooni Data mining of Students Withdrawal at University of Tehran, Focusing on Fee Paid Students (to prevent customer churn) Journal of Information Technology Management customer churn customer relation management educational data mining withdrawal |
| title | Data mining of Students Withdrawal at University of Tehran, Focusing on Fee Paid Students (to prevent customer churn) |
| title_full | Data mining of Students Withdrawal at University of Tehran, Focusing on Fee Paid Students (to prevent customer churn) |
| title_fullStr | Data mining of Students Withdrawal at University of Tehran, Focusing on Fee Paid Students (to prevent customer churn) |
| title_full_unstemmed | Data mining of Students Withdrawal at University of Tehran, Focusing on Fee Paid Students (to prevent customer churn) |
| title_short | Data mining of Students Withdrawal at University of Tehran, Focusing on Fee Paid Students (to prevent customer churn) |
| title_sort | data mining of students withdrawal at university of tehran focusing on fee paid students to prevent customer churn |
| topic | customer churn customer relation management educational data mining withdrawal |
| url | https://jitm.ut.ac.ir/article_53969_0368dcb86cf8dbb8091a8874402b45be.pdf |
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