ANALYSIS of ACCESSIBILITY INFLUENCE TO URBAN LAND NIR

• Main Author: (NIM 25105029), Ediyansyah
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/7731
• Institution: Institut Teknologi Bandung

Land value is information which necessary for DJP to specify PBB. Information of land value is applied as component of determination NJOP which is setting basis PBB. According KEP-533 the year 2000 it is mentioned that method applied in calculation value per m2 is comparison method with NIR (Indication Value of Mean) at certain zone, with variable, one of between it is accessibility. Accessibility interpreted as concept merging governing system to arrange land use geographically with transportation system connecting it. Accessibility is a procedural comfort scale or amenity of location arranges interaction land use one another and easy or its hard of the location is reached through transportation system. Accessibility always is related to travelled distance. If a place nearby other place, told accessibility between both the places is height. On the contrary, if both the places so far, accessibility between both low. <br /> <br /> <br /> <br /> <br /> <br /> Development of transportation science, travelled distance factor is not the only factor determining level of accessibility. There are some other factor of which can determine height the low of accessibility, between of time factor a real determined with availibility of transportation infrastructure, cost factor, factor of intensity arranges usage and earnings factor of man who is doing travelling. <br /> <br /> <br /> <br /> <br /> <br /> This research to analyse variables influence from accessibility to urban land value. Variable that is accurate was travelling time, road class, publik transport route and carriage volume. Data analysis applies spatial analysis and statistical analysis. Result of analysis indicates that travelling time, road class, number of publik transport routes and carriage volume, influential manifestly to NIR. Based on spatial analysis and regression analysis, travelling time influential negativity, with regression coefficient value - 284.712,567; road class influential positive, with regression coefficient value 13.640,423; variable number of publik transport routes influential negativity, with regression coefficient value - 246.300,890; carriage volume variable of influential positive, with regression coefficient value 244.041,576.