Mapping Land Suitability for Sugar Cane Production Using K-means Algorithm with Leaflets Library to Support Food Sovereignty in Central Java

Abstract

Indonesia is the largest sugar importer country in the world, this is contrary to the government’s desire to realize sugar self-sufficiency. To overcome the dependence on sugar imports in order to support national food sovereignty, geographic information system technology (GIS) can be used to present information as material for consideration by the government in determining policies on the management of sugar cane land resources. The K-means algorithm is used to group regions according to production level, while the Matching method is for evaluating the suitability of sugarcane land. Presentation of data in the form of map visualization on the web using a new model in processing land data, where this model processes production grouping data, and land suitability class data in the form of GeoJSON then mapped with the help of Leaflets. This new model enables dynamic land data processing and visualization in the form of interactive maps. The results of the EUCS test for GIS mapping of Land Suitability and Cane Production are 3.23 (Satisfied) of the total score of 4, so this system can be accepted by the user.