In MAS with distributed architecture, Agents are employed to achieve task objectives through mutual coordination and collaboration. Since there is no centralized management authority to rely on, it is difficult to judge the reputation information of Agents. Beyond that, traditional reputation evaluation methods based on evaluation and feedback have some problems, such as the insufficient usage of feedback evaluation and the absence of feasible mechanism for credible feedback evaluation information, etc. To solve these problems, a comprehensive reputation calculation method is proposed in this study. Concerning about malicious evaluation submitted by individual users, the proposed algorithm first filters the service evaluation data by the CUSUM (cumulative sum) control chart theory, then integrates different dimension of evaluation data using information entropy method, after that, uses PageRank algorithm to measure the influence of individual. Finally, it gives the comprehensive reputation model incorporating feedback evaluation of truth value and individual influence. Simulation results show that the proposed method performs well in improving reputation computation accuracy and convergence as well as the resisting of malicious attacks.