Fuzzy set with similarity measure approaches are known to be effective in handling imprecise and
subjective information to solve decision making problems. Many methods have been introduced based on these two concepts. However, most methods do not take into account the reliability factor of the imprecise information in the evaluation process. In 2010, Zadeh coined the idea of Z-number that has the ability to consider the reliability factor or the level of confidence of human’s information expression. Since then, some decision-making methods have included this concept. In this paper, we present a new fuzzy decision making procedure by integrating the Jaccard similarity measure with Z-number to solve a multi criteria decision making problem. The conversion method of the Z-number based linguistic value to trapezoidal fuzzy numbers is used and the Jaccard similarity measure of the expected intervals of trapezoidal fuzzy numbers is applied to obtain the final decision. The feasibility of the methodology is demonstrated by investigating the preference factors that could influence customers to buy their preferred choice of car. The proposed methodology is applicable to solving decision making with a fuzzy environment to achieve a reliable and optimal decision.