Information System databases for Neuropsychology Tests: case study in Boston Naming Test

Shinta Estri Wahyuningrum, Augustina Sulastri, Ridwan Sanjaya

Abstract


In the field of psychology, determining the psychological condition of a person’s can be done using various types of tests. Neuropsychology test is a battery test that means every person should be taken 11 test in a moment. Each test has a different objective, as an example, The Boston Naming test is used to measure a person's ability in the language domain. The data stored for each data in the Boston Naming Test (BNT) is around 130 fields. Each test has different specific data. This makes the data grow rapidly and requires a database design that can accommodate this need.

There are many approaches can be done to store the database such a relational database and NoSQL database. When the data are stored using relational methods and amount of data are large, there can be a lack of time in both processing and tracking. This article proposes a system to store the result of the neuropsychological test using the NoSQL database approach with sample data in subtest BNT.

Keywords


Database, NoSQL, Neuropsychology, Statistical, BNT

Full Text:

PDF

References


B. Jose and S. Abraham, ”Exploring the merits of nosql: A study based on mongodb”, International Conference on Networks & Advances in Computational Technologies (NetACT), Thiruvanthapuram, 2017, pp. 266-271.

Z. Haishan and J. Xiaolian, ”Design and Implementation of College Consumption Analysis System Based on NoSQL Database,” 2018 International Conference on Computer Science & Education (ICCSE), Colombo, 2018, pp. 830-834.

Herrnansyah, Y. Ruldeviyani and R. F. Aji, ”Enhancing query per- formance of library information systems using NoSQL DBMS: Case study on library information systems of Universitas Indonesia,” 2016 International Workshop on Big Data and Information Security (IW- BIS), Jakarta, 2016, pp. 41-46.

D. Ramesh, E. Khosla and S. N. Bhukya, ”Inclusion of e-commerce workflow with NoSQL DBMS: MongoDB document store,” 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Chennai, 2016, pp. 1-5.

C. Yang, J. Liu, W. Hsu, H. Lu and W. C. Chu, ”Implementation of Data Transform Method into NoSQL Database for Healthcare Data,” 2013 International Conference on Parallel and Distributed Computing, Applications and Technologies, Taipei, 2013, pp. 198-205.

JVD’silva, FDeMoor, BKemme, ”AIDA-Abstraction fo rAdvanced In-Database Analytics,” 2018 Proceedings of the VLDB Endowment, 2018, pp. 1400-1413.

RK Lomotey, R Deters, ”Data mining from document-append NoSQL,” 2014 International Journal of Services Computing (IJSC), 2014, pp. 17-29.

L. Stanescu, M. Brezovan and D. D. Burdescu, ”Automatic mapping of MySQL databases to NoSQL MongoDB,” 2016 Federated Con- ference on Computer Science and Information Systems (FedCSIS), Gdansk, 2016, pp. 837-840.

Kessels R.P.C., & Hendriks M.P.H, ’Neuropsychological Assessment. In: Howard S. Friedman,” 2016 Encyclopedia of Mental Health, 2nd edition, Vol 3, pp. 197-201

deVent, N. R., Rentergem, J. A., Schmand, B. A., Murre, J. M., ANDI Consortium & Huizenga, H. M. ” Advanced Neuropsychological Diagnostics Infrastructure (ANDI): A Normative Database Created from Control Datasets, ” 2017, Frontiers in Psychology.

Zillmer Eric A., Spiers Mary V., Culbertson William C. (2008). Principle of Neuropsychology, Second Edition. Thomson Higher Education. United States of America

Zucchella Chiara, Federico Angela, Martini Alice, Tinazzi, Bartolo Michelangelo, Tamburin Stefano. (2018). Neuropsychological testing. Pract Neurol. http://pn.bmj.com/content/early/2018/02/22/practneurol-2017-001743#ref-list-1

Casaletto Kaitlin B and Heaton Robert K. (2017). Neuropsychological Assessment : Past and Future. Journal of the International Neuropsychological Society, 23, 778-790

Alyahya, R.S.W., & Druks, J. (2016). The adaptation of the Object and Action Naming Battery into Saudi Arabic. Aphasiology, 30 (4), 463 – 482. https://doi.org/10.1080/02687038.2015.1070947

Joao Ricardo Lourenco, Bruno Cabral, Paulo Carreiro, Marco Vieira and Jorge Bernardino. 2015. Choosing the right NoSQL database for the job : a quality attribute evaluation. Journal of Big Data. DOI 10.1186/s40537-015-0025-0

Xi Zheng, Min Fu, Mohit Chugh. 2017. Big data Storage and Management in SaaS applications. Journal of Communications and Information Networks, Vol.2, No.3. DOI : 10.1007/s41650-017-0031-9




DOI: https://doi.org/10.24167/sisforma.v6i1.2274

Refbacks

  • There are currently no refbacks.


Bookmark and Share


SISFORMA: Journal of Information Systems | p-ISSN: 2355-8253 | e-ISSN: 2442-7888 | View My Stats

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.