Penelitian & Abdimas

1. How to Train The Data Sing So That We Dance Again: The Case with Covid-19 (

For the Data Science & Innovation labs within International Business Engineering (IBE) program at Petra Christian University, our involvement with Covid-19 came when we learnt together in the BE4140 Project Business Analytics class (February – June 2020). In early March (Saturday 3/7/2020 WIB), we were contemplating to have a real-life project to predict the Covid-19 using data available from GITHub as prepared by John Hopkins Center for Systems Science and Engineering, and building a Dashboard using MicroStrategy Analytical Platform that allow the Data to tell stories and sing loudly with some kind of predictions of when this social distancing will end. This is the main purpose: to build a closed-loop Business Intelligence system since there are new data daily

2. Factors Affecting Customer Satisfaction and Loyalty in Online Food Delivery Service during the Covid-19 Pandemic: Its Relation with Open Innovation. J. Open Innov. Technol. Mark. Complex. 20217(1), 76;
Three IBE students: Hans Tanto, Martinus Maryanto, and Christopher Hanjaya, under Dr. Yogi Tri Prasetyo (Associate Professor V, School of Industrial Engineering and Engineering Management, Mapúa University, Adjunct Professor at IBE Program) conducted research, wrote a paper, and successfully published it in the open source Q1 Journal. 
Data Analysis of High School Students in Stella Maris (Surabaya), Mater Dei (Probolinggo), and Santa Maria (Malang) for Dharmaputri Association
By: Dra. Indriati Njoto Bisono, M.Sc., Ph.D.,  Dr. Ir. Drs.Ec. Hanijanto Soewandi, M.Sc., IBE students class of 2018
We use methodology taught in Business Analytics (BE4131) to help Dharmaputri Association to analyze three high-schools (SMA Santa Maria – Malang, SMA Mater Dei – Probolingo and SMA Stella Maris – Surabaya) that belong to Dharmaputri.

In particular, we collected (crawled) official data over several years from Departemen Pendidikan & Kebudayaan, build an Enterprise Data Warehouse (i.e., Warehouse Database), performed an ETL (Extract Transform Load) to build an OLAP data model, and quantitatively answer the research questions (supported by data).

All findings are presented in a Dashboard.