A spatial analysis of soybean land suitability using spatial decision tree algorithm

Soybean is one of the national strategic commodities because of its role as an income and nutrition source for Indonesian people. Until now, the performance of soybean agribusiness is still far from expectations, as indicated by stagnant production and increasing import. One of the problems of the soybean production to achieve self-sufficiency is the unavailability of land allocation that is intended explicitly for planting soybean. This work aims to evaluate the soybean land suitability in Bogor District, West Java Province, Indonesia using the spatial decision tree algorithm. The proposed algorithm has been applied to a spatial dataset consisting of a target layer that represents soybean land suitability and seven explanatory layers that represent land characteristics of Bogor District. The result is a spatial decision tree that generated 26 rules with accuracy of 92.73% and the relief variable as the root node.

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