Publikasi Scopus Covid-19 Per 14 Agustus 2024 (559 artikel)

Muharram A.P.; Taufikulhakim F.H.; Purwarianti A.
Muharram, Arief Purnama (57844053000); Taufikulhakim, Farhan Hilmi (57222619312); Purwarianti, Ayu (13104011100)
57844053000; 57222619312; 13104011100
Building a Simple COVID-19 Knowledge Graph in Bahasa Indonesia: A Preliminary Study
2023
2023 IEEE International Biomedical Instrumentation and Technology Conference, IBITeC 2023
159
164
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Universitas Indonesia, Faculty of Medicine, Jakarta, Indonesia; Institut Teknologi Bandung, School of Electrical Engineering and Informatics, Master Program of Informatics, Bandung, Indonesia
Muharram A.P., Universitas Indonesia, Faculty of Medicine, Jakarta, Indonesia; Taufikulhakim F.H., Universitas Indonesia, Faculty of Medicine, Jakarta, Indonesia; Purwarianti A., Institut Teknologi Bandung, School of Electrical Engineering and Informatics, Master Program of Informatics, Bandung, Indonesia
COVID-19 is an acute respiratory disease that has become a pandemic worldwide. Many studies have been conducted to enhance our understanding of COVID-19. However, the abundance of information obtained from these studies has resulted in information overload. In this study, we purposed a simple COVID-19 Knowledge Graph in Bahasa Indonesia as a way to reconstruct knowledge to combat this information overload. We used Bahasa Indonesia in our study to explore its potential for constructing a Knowledge Graph (KG). The construction of our KG involved manual curation of medical literatures and annotation of entities and relationships by the domain experts. The KG was implemented using Neo4J version 5. We successfully demonstrated our COVID-19 KG, which consists of 240 nodes and 276 relationships with 15 and 14 node and relationship labels, respectively. Accessing the information within the KG is made effortless through the use of Cypher queries in Neo4J. Further research is still needed to develop the KG into a larger and better one. However, our COVID-19 KG can serve as a basis for further development. © 2023 IEEE.
Bahasa Indonesia; COVID-19; knowledge graph
Knowledge graph; Bahasa indonesia; Curation; Domain experts; Further development; Indonesia; Information overloads; Knowledge graphs; Medical annotation; Medical literatures; Simple++; COVID-19
Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi, MECRT
ACKNOWLEDGMENT This work was supported by the Thesis Research Grant for Master’s degree, National Competitive Research Program Fund, Ministry of Education, Culture, Research, and Technology, Republic of Indonesia 2022.
Institute of Electrical and Electronics Engineers Inc.
979-835030242-4
Conference paper
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