Computational science is required for the development of technologies primarily focused on computational geometry. The method used for its development is the Voronoi diagram. Voronoi diagram is a method of sharing a map to a smaller area berdasaarkan shortest distance to the object. Voronoi diagrams are also used to divide the map into a smaller space or Voronoi cell. Voronoi cells may consider the object in the area as its nearest object. It has the bene???t of analyzing objects in the area that have potential in ???elds such as business development. Voronoi diagram has a variation of that order-1 and Higher Order Voronoi Diagram Voronoi diagram. Order-1 and Higher Order Voronoi diagram has the disadvantage that the dynamic nature and have high computing on Higher Order. The weakness is overcome by using a Voronoi diagram is the latest variation of Highest Order Voronoi Diagram (HSVD) which can be used for all orders Voronoi diagram. HSVD have bene???ts for identi???cation fartest point and the region, as well as the identi???cation of all distances for each region. However, these methods there is a shortage due to the fragmentation object can not be directly accessed because fragment has a polygon shape. This resulted in accessing require high computing. So accessing fragment can use linear search for pengecekannya. Consequently make data searches to ???nd the region to be slow and takes a long time. Therefore, fragment needs index in order to reduce to a search region. Indexing is a data structure to improve the speed of data retrival operation. In this paper will present a index structure that incoperates Highest Order Voronoi Diagrams into Quadtree. Quadtree index used is capable of cutting more than half of the original data. This algorithm makes the search regions faster than before.