The analysis of variables which influence rent-value of units on multi-level commercial building based on 3D network data structure
Leksono, Bambang Edhi et al.
The value of business units on multi-level commercial building is influenced by physical and location factors. The physical factor variables could be easy identified from attribute data. However identifying location factor variable is more difficult because it requires geometric calculation based on the model of topological relationship among units on multi-level commercial building (room, vertical conduits and corridor). The objective of this research is build data structure of 3D network, which is weighted by euclidian-distance and timedistance to identify the location factor variable coefficient using shortest path analysis of djikstra algorithm. Subsequently, the results of variable identification analyzed using multiple regression analysis to derive topological relationship and variable which most influencing rent-value of units. This research shows the weight of euclidian-distance of network has more influence to rentvalue rather than the time-distance of network. Variables: floor level has negatively effect, amount of access has positively effect, distance to entrance has negatively effect, distance to escalator has negatively effect and distance to elevator has negatively effect to rent-value of units with 95% confidence level signification.
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