Pemodelan Pengetahuan Graph Database Untuk Jejaring Penelitian Kesehatan di Indonesia
DOI:
https://doi.org/10.30865/mib.v4i3.2183Keywords:
Health Research, Graph Data Base, NetworkAbstract
Health research is research approved in the medical field. Health research in Indonesia is increasingly being approved by researchers in Indonesia, therefore research is stored in repositories. Many health research journal repositories are available, but there is minimal research for analysis and modeling in the health research network in Indonesia. This research proposes a knowledge modeling with Neo4j graphic database to implement it. In this study, data obtained from the SINTA Journal with web scraping techniques. The purpose of this research is to produce network knowledge using CQL (Chyper Query Language) which is useful in the medical field. The results of this study are expected to be useful for the government, academics, researchers, or the public for health research network researchers in Indonesia. The results of research testing modeling of health research network knowledge using a graph database of 95.2% said very good
References
Rahmi Surayya, “Pendekatan kualitatif dalam penelitian kesehatan,†J. Kedokt. dan Kesehat. Malikussaleh, pp. 75–84, 2018.
R. Sistem, Y. Sahria, and D. H. Fudholi, “Analisis Topik Penelitian Kesehatan di Indonesia Menggunakan Metode LDA,†JURNAL RESTI., vol. 1, no. 10, pp. 336–344, 2021.
P. W. Wirawan and D. E. Riyanto, “Kajian Implementasi Graph Database pada Rute Bus Rapid Transit,†J. Nas. Teknol. dan Sist. Inf., vol. 3, no. 3, pp. 313–319, 2017, doi: 10.25077/teknosi.v3i3.2017.313-319.
H. Lu, Z. Hong, and M. Shi, “Analysis of film data based on Neo4j,†Proc. - 16th IEEE/ACIS Int. Conf. Comput. Inf. Sci. ICIS 2017, pp. 675–677, 2017, doi: 10.1109/ICIS.2017.7960078.
J. Zhao, Z. Hong, and M. Shi, “Analysis of disease data based on Neo4J graph database,†Proc. - 18th IEEE/ACIS Int. Conf. Comput. Inf. Sci. ICIS 2019, pp. 381–384, 2019, doi: 10.1109/ICIS46139.2019.8940247.
C. Constantinov, L. Iordache, A. Georgescu, P. S. Popescu, and M. Mocanu, “Performing social data analysis with Neo4j: Workforce trends and corporate information leakage,†2018 22nd Int. Conf. Syst. Theory, Control Comput. ICSTCC 2018 - Proc., pp. 403–406, 2018, doi: 10.1109/ICSTCC.2018.8540645.
V. Bajaj, R. B. Panda, C. Dabas, and P. Kaur, “Graph Database for Recipe Recommendations,†2018 7th Int. Conf. Reliab. Infocom Technol. Optim. Trends Futur. Dir. ICRITO 2018, pp. 276–281, 2018, doi: 10.1109/ICRITO.2018.8748827.
P. W. Wirawan, D. E. Riyanto, and K. Khadijah, “Pemodelan Graph Database Untuk Moda Transportasi Bus Rapid Transit,†J. Inform., vol. 10, no. 2, pp. 1271–1279, 2016, doi: 10.26555/jifo.v10i2.a5072.
R. Wita, K. Bubphachuen, and J. Chawachat, “Content-Based Filtering Recommendation in Abstract Search Using Neo4j,†ICSEC 2017 - 21st Int. Comput. Sci. Eng. Conf. 2017, Proceeding, vol. 6, pp. 136–139, 2018, doi: 10.1109/ICSEC.2017.8443957.
Y. Ma, Z. Wu, L. Guan, B. Zhou, and R. Li, “Study on the relationship between transmission line failure rate and lightning information based on Neo4j,†POWERCON 2014 - 2014 Int. Conf. Power Syst. Technol. Towar. Green, Effic. Smart Power Syst. Proc., no. Powercon, pp. 474–479, 2014, doi: 10.1109/POWERCON.2014.6993713.
C. I. Johnpaul and T. Mathew, “A Cypher query based NoSQL data mining on protein datasets using Neo4j graph database,†2017 4th Int. Conf. Adv. Comput. Commun. Syst. ICACCS 2017, pp. 4–9, 2017, doi: 10.1109/ICACCS.2017.8014558.
I. N. P. W. Dharmawan and R. Sarno, “Book recommendation using Neo4j graph database in BibTeX book metadata,†Proceeding - 2017 3rd Int. Conf. Sci. Inf. Technol. Theory Appl. IT Educ. Ind. Soc. Big Data Era, ICSITech 2017, vol. 2018-Janua, pp. 47–52, 2017, doi: 10.1109/ICSITech.2017.8257084.
I. Com, STATE OF HEALTH INEQUALITY Indonesia. 2017.
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