DEVELOPMENT OF ONTOLOGY FOR INDIGENOUS KNOWLEDGE CASE STUDY: LOCAL MEDICINE FROM LOCAL TRIBE IN INDONESIA
<p align="justify">Indigenous knowledge has been widely used as a basis for local decision making in various sectors and passed down through generations. Indonesia with diverse ecosystems have diverse local knowledge that become potential to be utilized and developed in knowledge man...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/28576 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | <p align="justify">Indigenous knowledge has been widely used as a basis for local decision making in various sectors and passed down through generations. Indonesia with diverse ecosystems have diverse local knowledge that become potential to be utilized and developed in knowledge management. Unfortunately, this utilization is not maximal yet due to several factors, such as the diversity in dissemination and transmission of indigenous knowledge, the diversity of philosophical and cultural backgrounds, the transmission of intergenerational knowledge through oral and culture practice, and less indigenous people’s involvement in indigenous knowledge development. <br />
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To improve this utilization, a clear and explicit indigenous knowledge representation is required and one of the basis representation for knowledge management is ontology. Using METHONTOLOGY approach, modeling and implementation of ontology is developed to find patterns or concepts of local medicine knowledge. This ontology was evaluated syntactically using Protégé and Oops! reasoners. This ontology was evaluated semantically using SNAP SPARQL. This ontology evaluated the quality of ontology’s structure with OntoQA. This ontology also compared the ontology with the medicinal plant knowledge base of the Ministry of Health. <br />
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The result of this study is the implementation of ontology model for indigenous knowledge in local medicine consisting of 9 main classes, 30 subclasses, 76 relations, 27 attributes, and 427 instances in RDF format. Based on the evaluation result with four previous approaches, ontology has 100% consistency, correctness, and completeness based on ontology structure, language, and syntax; 100% consistency, correctness, and completeness based on competency questions; 71,70% relation wealth, 69,23% attribute wealth, 76,92% knowledge reach; and 77,02% suitability comparison. From the evauation result, ontology can be stated has fulfilled the purpose of research to get the concept of local medicine knowledge. <p align="justify"> <br />
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