E-procurement Performance Model for Construction Tendering: Multiple Linear Regression Approach

E-procurement is a popular enterprise information systems (EISs) that were implementing by many companies and governments in digital transformation era. E-procurement for the tendering process increases transparency and organizational performance. The objective of this paper is to utilize the web mining to gain insight from data patterns in e-procurement systems regarding procurement performance. Construction tender data from two central provinces in Indonesia: East Java and DKI Jakarta, are case studies to be absorbed from tender applications via web mining. The case studies data are processed using the multiple linear regression method to produce a predictive model for one of the effectiveness performance indicators: bidder appointment time. Four independent variables: contract price, number of participants, number of bidders, and number of revisions were proven to predict bidder appointment time significantly. The number of revisions has the most influence on bidder appointment time in terms of its coefficient value. The model can be used for tender scheduling, setting procurement targets, to resource planning.