Name : Dr. Jastini Binti Mohd Jamil
Phone: 04-9286365
Email: jastini@uum.edu.my
School: Quantitative Sciences
Substantive position: Senior Lecturer
Current Position: Co curriculum Coordinator
Current Department: UUM College of Arts and Sciences

Academic Qualification
2012, PhD Data Mining, University of Bradford, United Kingdom
2008, Master of Philosophy Management (M.Phil), University of Bradford, United Kingdom
2003, Master of Science Computer Sciences, Malaysia, Universiti Teknologi Malaysia
2001, Bachelor Degree Information Technology, Malaysia, Universiti Utara Malaysia

Awards & Recognitions
Anugerah Perkhidmatan Cemerlang, Universiti Utara Malaysia, 2014, Universiti
Journal Reviewer, Elsevier, 2017, Antarabangsa
Juri Pertandingan Inovasi Pengajaran 2017, UTLC Universiti Utara Malaysia, 2017, Universiti
EMAS- Pertandingan Invention, Innovation and Design On E-Learning (IIDEL), MEIPTA, 2017, Antarabangsa

Overview
Dr. Jastini Mohd Jamil is a senior lecturer and researcher in Data Mining at School of Quantitative Sciences, Universiti Utara Malaysia. She received his Ph.D in Data Mining from University of Bradford in 2012. Her doctoral thesis work (Partial Least Squares Structural Equation Modelling with Incomplete Data: An Investigation of the impact of statistical and computational imputation methods) with Dr. James Wallace and Dr. Reza Abdi used models drawn from customer index satisfaction domains using structural equation modeling to compare statistical imputation methods and computational imputation methods. She also holds a Master of Computer Sciences with focused on data mining, rough sets and neural networks from Universiti Teknologi Malaysia, and a Bachelor degree in Information Technology (networking) with honours from Universiti Utara Malaysia. Her research interests are solving problems in diverse area using data mining, decision support system and statistical techniques. Her other interests include structural equation modeling, partial least squares, neural networks, rough sets, data pre-processing, handling missing data and forecasting.

Research Area
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Area of Expertise
1. data mining
2.data preprocessing/preparation
3.partial least square SEM