<![CDATA[PT. XYZ is a company engaged in the field of port services that serve the activity loading/unloading dry bulk vessels loaded. Based on the interview with the company known that the arrival of ships per day up to 5 ships with a length of service up to 3 days per vessel is still causing queues on dry bulk terminal. The research method used was the distribution of test data on the number of boat arrivals, the data between the time of arrival of the ship, and the ship service time approaches poisson and exponential distribution patterns to determine the queuing model used. The results obtained by the data of ship arrivals follow Poisson distribution and arrival time data between ship and ship service time follows an exponential distribution with the queuing model M/M/3: FIFO/∞/∞. Calculation of the attributes of the queue is known that λ = 0.7875 μ = 0.3168 with the average number of vessels in the queue Lq ≈ 3.3576 as 4 boats and ships an average time while the system is 7.4202 days. With the aspiration level of company that the average number of vessels in the queue no more than one vessel and the average ship time while the system is no more than 4 days, the queuing problem is solved by giving suggestions to increase the number of dock as much as 1 unit. With this addition then, the average number of vessels in the queue to be one ship, while the average time for the ship to be in the system to no more than 4 days. This condition states that the problem of queues at the dry bulk terminal is in the category as desired by the company.]]>
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