Angelina Kurniati

Profile

In January 2006 Angelina joined the School of Computing at Telkom University, Indonesia as a lecturer. She has taught Computer Science at undergraduate level and supervised final year projects at both undergraduate and master level, and had been an Assistant Manager of the computer laboratories for four years. Angelina has been involved in several research projects in the University and lead several research grants funded by the Indonesia Higher Education Ministry (DIKTI). The main area of her research was data mining, information systems and process mining. The latest research grant entitled 'Study and implementation of process mining for business process audit', was funded by the Indonesia Higher Education Ministry (DIKTI) in a multi-year competitive grant (2014-2016). Angelina has authored and co-authored at least thirteen papers in process mining at national and international level of conferences and journals.

Angelina has undertaken a number of courses to support her study, in the area of knowledge and intellectual abilities; personal effectiveness; research governance and organization; and engagement influence and impact. Ethical approval and an NHS honorary contract are now in progress as part of the requirements to access the data of cancer patient treatments in PPM and PPM+. The final outcomes of this research will be new features in process mining tools and a methodology for analyzing variety as well as providing insight for system developers on the impact of user interface design.

Research interests

She is currently doing her PhD with a full scholarship from Indonesia Endowment Fund for Education (LPDP). Her PhD title is 'Implementing process mining to test the effects of user interface design to the actual care processes in e-health system'. The aim of this study is to explore and develop new tools and techniques in process mining suitable for testing the effects of user interface design on the provision of care. The research initially uses existing tools to examine evidence of actual cancer care patterns in PPM and PPM+, the systems of cancer patient pathways management in Leeds Cancer Center, as high volume (big data) e-health record sources, working with clinicians and system providers. The impact of systems design will be tested by selecting retrospective cohort data from systems which have different design features and the tools used to identify patterns where care can be shown to vary as a result. Angelina is now performing some experiments with the MIMIC-III dataset and exploring the relationship of user interface design with process analysis, whilst access to the PPM and PPM+ datasets are granted. Angelina has had a literature review of process mining in oncology published in an IEEE conference proceeding within her first year of study.

 

Research groups and institutes

  • Artificial Intelligence