In this paper, the communication energy efficiency (EE) of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided integrated sensing and communications (ISAC) systems underlying a near-field scenario is investigated, where the dual-functional base station (DFBS) serves multiple users and senses multiple targets simultaneously. To ensure user fairness, we formulate an optimization problem that maximizes the minimum (max-min) communication EE while satisfying the minimum target illumination power requirement, the maximum transmission power budget, and the hardware constraints of STAR-RIS under its three operation modes. The formulated max-min optimization problem exhibits non-convexity due to the high coupling among the optimization variables. So as to resolve this issue, the fractional programming is first leveraged to transform the objective function into a more tractable structure. Then, the original max-min problem is transformed into an equivalent maximization problem via introducing the auxiliary variable. Next, we propose an alternating optimization framework to decouple the newly reformulated maximization problem into several sub-problems, which are optimized iteratively until convergence. Finally, the outcomes from the simulations are executed to confirm the advantages and effectiveness of the schemes we have introduced.