Arqawi, Samer M. (57216524429); Abu Rumman, Mohammed A. (57223123537); Zitawi, Eman Akef (57917254800); Rabaya, Anees Husni (57917061300); Sadaqa, Ahmad Saleh (57972864100); Abunasser, Basem S. (57841947400); Abu-Naser, Samy S. (26533902900)
Journal of Theoretical and Applied Information Technology
PREDICTING EMPLOYEE ATTRITION AND PERFORMANCE USING DEEP LEARNING
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Little Lion Scientific
Industrial Management Department, Palestine Technical University-Kadoorie, Palestine; Business Administration Department, Faculty of Business, Al- Balqa' Applied University, Jordan; Researcher in educational administration, College of Graduate Studies, Department of Educational Administration, Arab American University Palestine, Palestine; the Health Administration Department, Al Quds Open University, Palestine; Arab American University, Higher Education College, Strategic planning programme, Palestine; University Malaysia of Computer Science & Engineering (UNIMY), Cyberjaya, Malaysia; Faculty of Engineering and Information Technology, Al-Azhar University, Gaza, Palestine
Arqawi S.M., Industrial Management Department, Palestine Technical University-Kadoorie, Palestine; Abu Rumman M.A., Business Administration Department, Faculty of Business, Al- Balqa' Applied University, Jordan; Zitawi E.A., Researcher in educational administration, College of Graduate Studies, Department of Educational Administration, Arab American University Palestine, Palestine; Rabaya A.H., the Health Administration Department, Al Quds Open University, Palestine; Sadaqa A.S., Arab American University, Higher Education College, Strategic planning programme, Palestine; Abunasser B.S., University Malaysia of Computer Science & Engineering (UNIMY), Cyberjaya, Malaysia; Abu-Naser S.S., Faculty of Engineering and Information Technology, Al-Azhar University, Gaza, Palestine
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Deep learning; Employee Attrition; Machine Learning; Prediction
