Prediction Data Mining Technique and Administrative Efficiency of Universities in Rivers State, Nigeria
Vol. 3, Issue 1, 2019, pp. 18-28. ISSN – 2672-4693 (print) 2672-4685 (online)
The study surveyed Prediction Data Mining Technique and Administrative Efficiency of Universities in Rivers State. The cross sectional survey design was adopted. The population of this study consist of (180) Management staff of the three universities in Rivers State, they includes, the Vice Chancellors, Registrars, Deans of Faculties and Head of departments of the universities. Taro Yamane formalar was used to determined a Sample Size of One Hundred and Twenty Four (124) Management staff of the universities that constituted the Unit of Analysis of the study. Research questions were used to determine to what extent Prediction Data Mining Technique enhanced Administrative Efficiency of Universities in Rivers State. The Null Hypotheses was therefore employed to predict the relationship between Prediction Data Mining Techniques and Administrative Efficiency of Universities in Rivers State. This was achieved using Linear Regression Analysis which indicated that there is a strong positive relationship between Prediction Data Mining Techniques and Administrative Efficiency of Universities in Rivers State. It is therefore concluded that Prediction Data Mining Techniques is an effective tool to improve Administrative Efficiency of universities in Rivers State. The research further, recommended that Prediction Data Mining Techniques should be properly implemented in the Database of the Universities in Rivers State to enhanced Administrative Efficiency of the Universities.
Keywords: Prediction Data Mining Technique, Database, Cost Effectiveness and Decision Quality
