<![CDATA[This research aims to produce a decision support system to reduce traffic jams through U-turn layout engineering. We carried out data collection by recording traffic at the research site and conducting interviews through questionnaires submitted to the sources. System development stage, where this stage is divided into three major stages according to the method used, namely the RAD method. The three major stages are requirements planning, workshop design, and implementation. Based on the research results, it was found that the modeling of traffic passed by a U-turn can be identified through calculation graphs of volume, speed, density, capacity, degree of saturation, and geometric delay. Traffic flow engineering is implemented by modeling eight open U-turns, which are then eliminated or closed one by one in order to increase vehicle speed and reduce delays on that road section. We also carried out contraflow modeling for comparison. However, the results obtained were no better than U-turn elimination. The largest average number of motorbikes at the end of the week was only 300 motorbikes on Saturday. Meanwhile, the largest average of motorbikes on weekdays was 400 motorbikes on Thursday. The design combines two WFA methods and the fuzzy logic method to present several alternative decisions in the form of final values and bar graphs. These alternatives can be used as material for expert consideration in decision-making. A graph can serve as a benchmark when eliminating U-turns and testing contraflow on the road. Eliminating U-turns and testing contraflow on the road can provide an alternative decision solution using the largest graph.]]>
