Business process modelling with the Source-Transaction-Agent (STA) data modelling - Ibrahim bin Mohamed (Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 2013)
Business process management is becoming popular in business, and offers effective and efficient operations. Business process modelling is a way of representing an organisation to enable its analysis and improvement. A business-friendly modelling is very helpful for business people, and can also act as a communication tool between them and the technical IT people. This research aims to solve the problem of developing a data model that can give more accurate answer (to accurately reflect the real world), facilitates user participation and its ability (in terms of effectiveness and efficiency) to reflect the business process. A new data model, called the Source-Transaction-Agent (STA) data model, is introduced as a modelling technique for business process modelling. STA data model uses business metadata to assist business and IT persons to communicate and participate effectively and efficiently in the business data modelling of a system development process. This research proposes the STA data model, and validates it through its accuracy, readiness, effectiveness, and efficiency. The data model design uses relational database concept and semantic data modelling, developed by combining the Resource-Event-Agent (REA) data model and the form-based approach. Entity Relationship Diagram (ERD) is used as the benchmark for the STA. The Readiness-Effectiveness-Efficiency-Accuracy Model (REEAM) is introduced as the evaluation in assessing the acceptance of the proposed model (the STA data model). The findings on the evaluation of the STA data model show positive results, especially for effectiveness and efficiency. Scores for reliability are good, showing high reliability. These show positive acceptance of the participants towards the STA data model. The outputs of this research (REEAM, STA data model and as a benchmark for future researches) should ease the system development process and data modelling technique in terms of effectiveness-efficiency-accuracy, and increases user participation.