No traffic-signal intersection located on Jalan Serang and Jalan Curug, Tangerang Regency often causes traffic congestion. Many side barriers activities of vehicles inhibit the movement of traffic flow.  The toll-road access, which is not far from the intersection, makes the queue long enough to enter Jl. Raya Serang also affects the performance of the surroundings. The study aims to determine the performance of the above intersection this time, which is measured by the capacity, degree of saturation, speed, queuing opportunities, density, and level of services. Field surveys and further analysis of the calculations that have been carried out show the intersection performance. The peak traffic volume occurred on Wednesday, February 5 2020, at 3877 pcu / hour at 07.00 - 08.00 WIB, with a capacity (C) of 2937 pcu / hour. From the available data, the DS value is 1.32. at the Service level F.

The development of road capacity is not in line with the development of the population and the increase in the number of vehicles. This has become a classic problem of transportation in the big cities of Indonesia, including in East Java Province. The existence of road capacity in accommodating vehicles must be resolved. One way to accommodate the number of vehicles is through the toll road. But comfortable conditions of the toll road can cause accidents. One factor causing this is the driver's behavior factors, as the toll road is a freeway, they tend to drive carelessly. On the other hand, high planning standards make the difference between toll roads and ordinary highways. Yet barrier-free road does not mean that the traffic accident problem can be resolved properly. This study aims to determine how significant is the influence of driver behavior factor in causing accidents. The methodology is done by analyzing the data using statistical methods. Based on the accident data obtained, a mathematical model with multiple linear regression analysis is made. The model connects the number of traffic accidents on the Surabaya-Gempol toll road with the number of accidents caused by driver factors. The results showed that the factors causing the accident were caused by less anticipated driver factors, carelessness, drowsiness, drunkenness, distance, etcetera. This variable has a significant effect on traffic accidents at Surabaya-Gempol Toll Road by 54%.

Traffic accidents are events that are not expected to involve at least one motor vehicle on a road and resulted in material losses, even to swallow the loss of life (source: Kadiyali, 1973). Therefore, the research team was interested in the theme of research related to the identification of Accident-prone Areas/Dots Black Spot as the basis for the creation of a technical Manual Handling accident (Accident Prone Area case study in the city of Surabaya of East Java province) in order to overcome the accident so as not to continue to increase. The purpose of research can determine the condition of the existing road indicated on the accident-prone areas. So that the existing problems in the field can be immediately made known to the handling of the proposal in the form of the Handbook. Methods of research conducted by the research team in this study is to identify existing conditions in order to know all the problems that occur in the field that causes a lot of accidents. The results of the identification / field surveys can be known perangkingan worst location on the basis of the number of accident victims. The location was ranked first to third is streets A.Yani value EAN 1467 (ranking first location) and has a value of 10,003 black spot; Kalianak roads EAN value 1266 (ranking second location) and has a value of 38,662 black spot; roads Mastrip EAN value in 1257 (ranked third) and had a 7138 value of the black spot. Value of the accident rate on the roads.A. Yani of 25.008; Mastrip Streets of 12.746; and Kalianak roads of 1266. Troubleshooting strategies applied divided 3 time periods, i.e. short term strategies, medium-term and long-term. The Division is performed based on the level of difficulty of the work and the magnitude of the costs incurred.

This paper aims to investigate the effect of railway development on the Indonesia national economy with Input-Output analysis. The data used in this study are Input-Output data from 2000 to 2010. Input-Output data analysis generates contribution, value added, intermediate input, final input, linkage and multiple impacts of a railway to other modes of transportation and national economy. The result of Input-Output data analysis concludes that the railway has forward and backward linkage to various sub-sectors, therefore it can become a superior sub-sector to increase national economic growth. The research results find out that if there is a development or investment in the railway subsector of IDR. 1 billion, this, will, therefore, give impact to: (a) the amount of economic output will increase into IDR 1.633767 billion; (b) the income of the society members will become IDR. 362,507 million; (c) will upgrade the employment opportunities into 9.556 people. Accordingly, there is a need to modify the government budget (APBN) that will focus primarily on developing railway transportation, both in goods and passenger vehicles.

Infrastructure is one of the supporting activities of transportation, such as airports, halte, terminals, and port buildings. The port terminal is one of the transportation infrastructure buildings used by passengers when they travel. The port terminal is expected to be able to provide good facilities for passengers while waiting for transportation. For this reason, it is necessary to do a model of passenger satisfaction on the performance of the passenger terminal in order to know what factors influence passenger satisfaction. The measurement of passenger satisfaction uses the classic assumption test method, and also tests the validity and reliability of the questionnaire submitted to the passenger. From the research that has been done, we get the final model of Passenger Satisfaction on the Service Performance of the Gapura Surya Nusantara Passenger Terminal as follows: Y1 = 62.325 + 0.714X1 + 0.020X2 + 0.040X5 + 0575X6 + 0.218X8 + 0.134X9 + 0.356X11 + 0.550X13 + 0.476 X14 + 0.488X17 - 0.658X19, the model is influenced by nine variables.