Ontology-Based Reasoning for Defining the Quality of Software Product

In the CHAOS report 2020 by the Standish Group, the significance of "a good team" is underscored as a critical determinant of project success. Previous research has indicated that team quality directly influences the outcomes of products delivered by each team. Hence, there is a need for automated identification to ascertain product quality based on team quality, facilitating data processing for users without the need for manual calculations, which can be time-consuming. Ontology emerges as one of the reasoning methods to address this issue. This study proposes an ontology method utilizing Protege tools to identify product quality based on team quality. It involves processing data from team development to determine levels, calculating total team dysfunction scores, normalizing values, and categorizing team quality and product quality using Semantic Web Rule Language (SWRL) rules. The experimental results demonstrate that employing ontology with Protege achieves an accuracy rate of 64,63%. Thus, the findings suggest that employing the ontology method can effectively determine product quality based on team quality within software development teams.