<![CDATA[Queue associated with all aspects of a situation where customers have to wait for a given service, such as the queue with the arrival of customers in groups providing mass broadly in the real world, for example, the elevator in the buildings, visitors to the amusement park, air cargo shipments, and bus transporting. As a result of inaccuracy determine the number of servers in a queue can result in the number of customers who are not served. Queues models discussed in this study is the queue with the arrival of customers in groups.follows a Poisson process. The number of subscribers in each group is a random variable (X) and the time between the arrival of a customer using exponential distribution. The service time using Erlang distribution with parameter m (Em), the processing served by many server (C). This study uses simulation to analyze the average customer wait time in the queue, the average waiting time of customers in the system, the average number of customers in the queue, the average number of customers in the system and the probability of a busy server. The purpose of this research is to create a queue simulation model M [X] / Em / C so it can find the queue characteristics derived from the settlement with the simulation]]>
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