CLASSIFICATION ANALYSIS FOR LAND SUITABILITY USING LINKED OPEN DATA

Land suitability is one of a solution to get alternative solutions to get maximum results. Land suitability is
obtained by applying classification rules based on several factors, such as: nutrients, erosion hazard,
temperature, flood hazard, and root media. The analysis will classify a land based on its order class into 2,
such as: suitable (S) and non-suitable (N). Spatial analysis for land suitability usually put together all the
required spatial data into one source first, and then analyzes it using land evaluation rules. However, the
concept of linked open data can create structure that are connected between data from different sources,
including applying classification rules to these data. Information related to the required attributes can be read
using LOD concept. The formulation of the problem in this study is how to classify the suitability of a location
for rice plants, if the data to be used as measuring variables are at different storage sources. This research
used a coordinate of an area as an identity that is used as a linked between different sources. In addition, it
will obtain the information that is needed for land suitability then classification rules are applied based on
information obtained from that location.