Queue process is a process related to the arrival of customers in a service facility, waiting in line queue if it cannot be served, get service and finally leaves the facility after being served. Research on the queue process can be seen directly through the queue system. Queue models and their distribution were obtained using the Sigma Magic program. The model of the vehicle queue system at the Muktiharjo Automatic Toll Gate is (NORM/NORM/4):(GD/∞/∞). Based on the values of the queue system performance measures obtained through the MATLAB GUI program as a whole it can be concluded that the queue of vehicles at the Muktiharjo Automatic Toll Gate has a condition where the average number of vehicles estimated in the system every 30 minutes is 99,2564 vehicles. The average number of vehicles in the queue system every 30 minutes is 98,2557 vehicles. The waiting time in the system is estimated to be around 15,51732 seconds. The estimated waiting time in line is around 15,36084 seconds. The queue system has a busy opportunity for 63.2849%. The simulation of the vehicle queue system at the Automatic Toll Gate of Muktiharjo Toll Gate by using ARENA is optimal with 4 automatic toll booths.

No abstract

Queue process is a process related to the arrival of customers in a service facility, waiting in line queue if it cannot be served, get service and finally leaves the facility after being served. Research on the queue process can be seen directly through the queue system at the automatic toll booth Muktiharjo. Queue models and their distribution were obtained using the Sigma Magic program. The model of the vehicle queue system at the Muktiharjo Automatic Toll Gate is (GAMM/ GAMM/ 4): (GD/ ∞/ ∞). Based on the values of the queue system performance measures obtained through the MATLAB GUI program as a whole it can be concluded that the queue of vehicles at the Muktiharjo Automatic Toll Gate has a condition where the average number of vehicles estimated in the system every 15 minutes is 25,5646 vehicles. The average number of vehicles in the queue system every 15 minutes is 24,5639 vehicles. The waiting time in the system is estimated to be around 7,99332 seconds. The estimated waiting time in line is around 7,68042 seconds. The queue system has a busy opportunity of 63.2849% and the remaining 36.7106% is a chance the queue system is not busy. The simulation of the vehicle queue system at the Automatic Toll Gate of Muktiharjo Toll Gate by using ARENA is optimal with the number of service points as many as 4 automatic toll booths. Keywords: Automatic Toll Booth, Queue, Gamma Distribution, Performance Size, Queue Simulation

—Mobile robots have been widely applied in the industrial world. Mobile robots are proven to help humans work, especially repetitive ones. A robot needs to plan its trajectory to move as desired, a concept that requires path planning. Path planning is a non-deterministic problem that plays a role in finding a path to connect the system to the desired destination. The existing path planning algorithm proposes a path with sharp bends that make it difficult for the robot to maneuver so that it can still be optimized from the sides of the proposed path. One way is to make smoother turns so that the robot is not difficult to turn. Applying the interpolation method using b-spline makes the proposed path smoother. B-spline is a spline feature that provides a specific order and minimal support for domain partitioning. B-spline is applied to the Smoothing A*(SA*) algorithm, one of the breakthrough methods to produce smoother paths. As a result, SA* consistently produces paths shorter than the stateof-the-art by 0.957% and shorter than the baseline by 4.891%.