ANALISIS PERMINTAAN PERGERAKAN DI KABUPATEN DAERAII TINGKAT II SERANG

• Main Author: Gustiadi, E.M.Ricky
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/4580
• Institution: Institut Teknologi Bandung

<b>Abstract:<p align=\"justify\"> <br /> <br /> Future socio-economic, land use and urban planing data are important factor`\', in determining area transport system. From these information, transport demand analysis model can be made which is correlated do the existing transport system. Moreover, this model can be improved to make a forecasting of a better future transport system.<p align=\"justify\"> <br /> The district of Serang (Kabupaten Dati II Serang) is taken as the area of research due to the condition that it is an industrial area with a good dynamic transport system. It is expected that from the chosen samples, the resulted model can be applied to the other district (areas ) with similar conditions.<p align=\"justify\"> <br /> The chosen data area origin and destination matrixes, friction factors, and socio-economic year of 1994. These data analysed by using chose structure to forecast transport demand. The model use four steps of transport planning model (trip generation, trip distribution, modal split, trip assignment ), SPSS for windows 5.0 software and TRANPLAN/NIS program to forecast transport system<p align=\"justify\">. <br /> The result of statistical test shows that Mean Square Error (MSE) < 3%. This indicates that the sample of origin and destination data are valid for trip generation and trip attraction, so the data are representative to forecast trip production and attraction for every single zone in the future (proven by a positive coefficient correlation ; 0.85389 R2 0.97464).<p align=\"justify\"> <br /> Based on the statistical analysis and analysis of transport planning model, the existing transport network of the district of Serang would not be able to accommodate the future traffic assignment demand if it would not be improved following the forecast future traffic and transport.