In the DSSfPS model, an inference engine is used to obtain the results (risk levels, PSSI value, and recommendations) by matching the rule sets in the knowledge base and the data available in the working memory. The method applied to design the inference mechanism is forward chaining. Forward chaining works by processing the data first and then using the rules in the knowledge base to draw new conclusions from these data [16,17]. This study applied forward chaining because it operates via a top-down approach, which takes the data available in the working memory and then generates results based on the satisfies conditions of the rules in the knowledge base. In the DSSfPS model, the inference engine performs the following functions: