#TITLE_ALTERNATIVE#

• Main Author: WIJAYA (NIM : 15413002), HADIYAN
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/27624
• Institution: Institut Teknologi Bandung

The Trans Java toll road infrastructure development serves as one of the prioritized development programs in the Jokowi era that has caused development of urban areas [in Java]. This phenomena can be identified through the transformation of periurban areas with urban and rural characteristics that has become more urban or otherwise known as periurbanization. In addition, other factors such as population, economy, social, environment, and institutions also contribute in influencing the change of the periurban characteristics. This study aims to identify transportation infrastructure influences towards the periurbanisation in Java. The method of analysis used in this study includes descriptive analysis to describe the urban characteristics in Java, r-pearson correlation method to identify the correspondation of urban characteristics found on ground with data from literature study, cluster analysis to identify the urban and periurban groups, and multiple regression analysis to identify the extent of the influence of transportation infrastructure towards periurbanisation. This study shows that there is a high diversity of urban characteristics in Java. This study also identifies the characteristics of periurbanisation in Java. Lastly, this study concludes that transportation infrastructure plays a significant role in influencing periurbanisation in Java. Based on such results, this study recommends the integration of road infrastructure and other public transportation services in order to fulfill the needs of transportation services in periurban areas and reduce the dependency of private transportation. This integration could thus reduce the rate of urban sprawl as a result of the growing forces of urban development. <br /> <br /> <br /> <br /> <br /> Keywords: Periurbanization, transportation infrastructure, cluster analysis, multiple regression <br />