A MULTICRITERIA INDEX USING NEURAL NETWORK TO EVALUATE THE POTENTIAL LANDS OF MAIZE

The criteria for planting maize should be consistent with sensible and ecological to determine the potential lands. However, there is still a lack of proven methodology this evaluation. purpose analysis was parameters that affect multi-criteria decision maize, aim new method on land suitability analysis. proposed based GIS-analysis management such as distance from roads, rivers, slope, LULC, elevation, soil type, NDVI, SAVI, rainfall, temperature. We have found sample 4590 in Tuban, East Java, Indonesia. Based above criteria, has been classified into four groups according FAO. Moreover, we analyzed done using Neural Network. Results showed integrated AHP Network evaluate lands inferred 66.7 percent study area highly suitable, 30.2 were moderately 3 marginally suitable Maize Cultivation Tuban Regency. approach presented can extended other areas also crops decision-making system.