A Knowledge Base System of Processing Local Cash Crops into Products for Community Enterprises
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Abstract
Plant economy is used for consumption and is the main occupation that generates income. However, in some seasons, production exceeds market demand. Processing can bring more benefits and value. Community enterprises often transform local plant economies into products. However, knowledge about processing needs to be improved for creating new products. If knowledge management for processing is organized into a system, community enterprises can access and utilize it effectively. This research aims to study the efficiency of an ontology knowledge-based system. The goal is to design and develop a semantic retrieval system that transforms local plant economies into efficient community enterprise products, technology development was conducted using protégé programming, applying technology linking relationships between technology structures in protégé format, and developing a semantic web retrieval system. Experts evaluated the technology structure. The overall assessment was highly accurate and appropriate, with an average score of 4.60 and a standard deviation of 0.51. The efficiency of the retrieval system was evaluated at a good level with an average precision 0.95, indicating a very high level of accuracy in retrieving information from relevant collections, recall of 0.90, indicating a high level of completeness of the retrieved data from collections, and F-measure of 0.92, indicating a very high level of retrieval performance. The well-structured technology design contributed to the efficient development of the semantic retrieval system. This supported knowledge about local plant economy processing for community enterprises and was a guideline for creating new products.
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