Ontology Data Modeling of Indonesian Medicinal Plants and Efficacy

Abstract views: 377 , PDF downloads: 327
Keywords: data model, knowledge, medicinal plant, ontology

Abstract

People use medicinal plants for as early prevention and treating disease. Medicinal plants must be careful not to cause side effects, so knowledge is needed. Medicinal plant knowledge is stored using an ontology data model. In some ontology studies, there are still shortcomings in managing information, namely the absence of a relationship between scientific terms related to medicinal plants and phrases already known to the public. Hence, it is necessary to have this relationship. In other studies, there is no information related to disease protein, so this research also develops ontologies to enrich knowledge about medicinal plants and their efficacy. Based on the results, the developed ontology test can build a relationship between scientific terms of therapeutic pants and phrases that are known to the public. The public also knows which proteins affect a disease, so public knowledge about medicinal plants is getting wider.

Downloads

Download data is not yet available.

References

Badan Pengawas Obat dan Makanan (BPOM), “Potensi Obat Herbal Indonesia,” Bpom Ri, vol. 11, no. 88. 2020.

Haeruddin, H. Johan, U. Hairah, and E. Budiman, “Ethnobotany database: Exploring diversity medicinal plants of dayak tribe borneo,” in International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 2017, pp. 1–6, doi: 10.1109/EECSI.2017.8239094.

N. Hilal A. Syahrir, F. Mochamad Afendi, and B. Susetyo, “Efek Sinergis Bahan Aktif Tanaman Obat Berbasiskan Jejaring dengan Protein Target,” J. Jamu Indones., vol. 1, no. 1, pp. 35–46, Mar. 2016, doi: 10.29244/jjidn.v1i1.30594.

E. E. Ogheneovo and P. A. Nlerum, “Knowledge Representation in Artificial Intelligence and Expert Systems Using Inference Rule,” Int. J. Sci. Eng. Res., vol. 11, no. 4, pp. 1886–1900, 2020, [Online]. Available: https://www.researchgate.net/publication/347504395.

T. R. Gruber, “A Translation Approach to Portable Ontology Specifications,” Knowl. Acquis., vol. 5, pp. 199–220, 1993, [Online]. Available: http://ac.els-cdn.com/S1042814383710083/1-s2.0-S1042814383710083-main.pdf?_tid=28c5c43c-df11-11e2-b19c-00000aacb35f&acdnat=1372327738_c3518b0aab22af436aef0c5e3e2dd48e.

F. Z. Laallam, M. L. Kherfi, and S. M. Benslimane, “Using Ontologies to Overcoming Drawbacks of Databases and Vice Versa: A Survey,” Comput. Sci. Eng. An Int. J., vol. 3, no. 2, pp. 1–21, 2013, doi: 10.5121/cseij.2013.3201.

M. Uschold, “Ontology and database schema: What’s the difference?,” Appl. Ontol., vol. 10, no. 3–4, pp. 243–258, 2015, doi: 10.3233/AO-150158.

R. Gunawan and K. Mustofa, “Finding knowledge from Indonesian traditional medicine using semantic web rule language,” Int. J. Electr. Comput. Eng., vol. 7, no. 6, pp. 3674–3682, 2017, doi: 10.11591/ijece.v7i6.pp3674-3682.

D. W. Wardani, S. H. Yustianti, U. Salamah, and O. P. Astirin, “An Ontology of Indonesian Ethnomedicine,” Int. Conf. Information, Commun. Technol. Syst., pp. 47–52, 2014.

H. Satria, R. S. Priya, L. H. Ismail, and E. Supriyanto, “Building and Reusing Medical Ontology for Tropical Diseases Management,” Int. J. Educ. Inf. Technol., vol. 6, no. 1, pp. 52–61, 2012.

A. Fazriani, W. A. Kusuma, and I. Batubara, “Sistem Berbasis Pengetahuan Tumbuhan Obat Pusat Studi Biofarmaka,” J. Jamu Indones., vol. 4, no. 1, pp. 17–27, 2019, doi: 10.29244/jji.v4i1.88.

W. Tungkwampian, A. Theerarungchaisri, and M. Buranarach, “Development of Thai herbal medicine knowledge base using ontology technique,” Thai J. Pharm. Sci., vol. 39, no. 3, pp. 102–109, 2015.

H. Shojaee-Mend, H. Ayatollahi, and A. Abdolahadi, “Developing a mobile-based disease ontology for traditional Persian medicine,” Informatics Med. Unlocked, vol. 20, 2020, doi: 10.1016/j.imu.2020.100353.

G. Vadivu and S. Waheeta Hopper, “Ontology mapping of Indian medicinal plants with standardized medical terms,” J. Comput. Sci., vol. 8, no. 9, pp. 1576–1584, 2012, doi: 10.3844/jcssp.2012.1576.1584.

N. Kaewboonma, T. Supnithi, and J. Panawong, “Developing ontology for Thai Zingiberaceae: From taxonomies to ontologies,” 14th Int. Conf. Electr. Eng. Comput. Telecommun. Inf. Technol., pp. 596–599, 2017, doi: 10.1109/ECTICon.2017.8096308.

A. Khamparia, B. Pandey, and V. Pardesi, “Performance analysis on agriculture ontology using SPARQL query system,” 2014 Int. Conf. Data Min. Intell. Comput. ICDMIC 2014, 2014, doi: 10.1109/ICDMIC.2014.6954258.

N. Kumar and S. Kumar, “Querying RDF and OWL data source using SPARQL,” 2013 Fourth Int. Conf. Comput. Commun. Netw. Technol. ICCCNT, 2013, doi: 10.1109/ICCCNT.2013.6726698.

S. Gqibani, N. Clarke, and A. L. Nel, “Motivation for developing a qualitative methodological basis for the analysis of historical curriculum changes,” IEEE Glob. Eng. Educ. Conf. EDUCON, pp. 637–644, 2016, doi: 10.1109/EDUCON.2016.7474617.

X. Li, Y. Zhang, J. Wang, and Q. Pu, “A Preliminary Study of Plant Domain Ontology,” Proc. - 2016 IEEE 14th Int. Conf. Dependable, Auton. Secur. Comput. DASC 2016, 2016 IEEE 14th Int. Conf. Pervasive Intell. Comput. PICom 2016, 2016 IEEE 2nd Int. Conf. Big Data, pp. 109–112, 2016, doi: 10.1109/DASC-PICom-DataCom-CyberSciTec.2016.36.

K. Mitsis, K. Zarkogianni, N. Bountouni, M. Athanasiou, and K. S. Nikita, “An Ontology-Based Serious Game Design for the Development of Nutrition and Food Literacy Skills,” Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS, pp. 1405–1408, 2019, doi: 10.1109/EMBC.2019.8856604.

A. Nugroho, “Membangun Ontologi Jurnal Menggunakan Protege,” J. Transform., vol. 10, no. 1, pp. 20–25, Jul. 2012, doi: 10.26623/transformatika.v10i1.66.

PlumX Metrics

Published
2022-08-13
How to Cite
[1]
R. M. Afifa, W. A. Kusuma, and A. Annisa, “Ontology Data Modeling of Indonesian Medicinal Plants and Efficacy”, intensif, vol. 6, no. 2, pp. 218-232, Aug. 2022.