<![CDATA[Global climate change has a significant impact on the agricultural sector, including horticulture, with climate fluctuations such as increased temperatures and changes in rainfall patterns potentially affecting crop productivity. Sustainable horticultural agriculture is important for safeguarding natural resources and reducing environmental impacts. However, challenges from climate change and variations in land conditions can affect horticultural crop production. Identifying crops that are suitable for the climate and land conditions is key to agricultural sustainability. An intelligent and adaptive approach is needed in selecting the right crops to grow in the face of climate change. This research develops an artificial intelligence application for the recommendation of horticultural crop types according to land conditions and climate change. The model built involves AHP and MFEP methods. The model takes into account various land parameters with weights determined through the AHP approach, allowing this AI application to provide accurate recommendations based on data and modeling. Based on the tests conducted, the system was able to produce analysis with an accuracy rate of 85%.]]>
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