Underlying the near-field scenario, this paper investigates the communication energy efficiency (EE) of the integrated sensing and communications (ISAC) systems which aided by simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). Aiming to achieve the purpose of maximizing the minimum (max-min) communication EE while satisfying the target minimum illumination power requirement, the maximum transmission power budget and adhering to the hardware limitations of the STAR-RIS, the dual-functional base station transmit and STAR-RIS beamforming matrices undergo a joint optimization process. The formulated max-min optimization problem exhibits non-convexity stemming from the intricate interplay and high degree of coupling within the optimization variables involved. So as to resolve this problem, the fractional programming method is first leveraged to convert the objection function into a more tractable structure, and then the original max-min problem is transformed into an equivalent maximization problem via bringing in the auxiliary variable. Next, an alternating optimization framework is introduced to decouple the newly rewritten maximization problem into two sub-problems for alternatively optimizing until convergence. Finally, the outcomes from the simulations are given to confirm the advantages and effectiveness of the scheme we have introduced.