<![CDATA[Indonesia’s food security is increasingly challenged by factors such as climate change, rapid population growth, and heavy reliance on imported food products. Despite being one of the most biodiverse countries in the world, Indonesia has not fully utilized the potential of its native food crops. One of the major obstacles is the lack of organized and well-documented knowledge about these plants, as most of the information is still transmitted orally and scattered across various sources. To address this issue, this study introduces an ontology-based knowledge representation model for Indonesian food crops. The model is developed using the Methontology approach and implemented through the Protégé platform. It includes key classes such as Plant, PlantTaxonomy, PlantFactors, and FoodCropCategory, encompassing 100 individuals, 29 object properties, and 5 data properties. This ontology organizes important information such as taxonomic classification, planting season, soil type, altitude preferences, scientific names, and crop categories. The reasoning ability of the ontology was evaluated using SPARQL queries to determine its capability to answer domain-specific questions. The results demonstrated that the ontology could effectively represent semantic relationships and retrieve relevant knowledge. This structured and semantically enriched model is expected to enhance digital documentation, promote knowledge sharing, and support intelligent systems for managing food crop information in Indonesia.]]>
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