Enhancing query performance of library information systems using NoSQL DBMS: Case study on library information systems of Universitas Indonesia

Herrnansyah,; Ruldeviyani, Yova; Aji, Rizal Fathoni

doi:10.1109/iwbis.2016.7872887

Cited by 3 publications

(5 citation statements)

References 5 publications

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“…Cluster four contains the cases no. 4 [47], 14 [51], 16 [53], 23 [56], 33 [70], 34 [75] and 35 [60]. During the observation and further examination of each of those, a similar distinction as in the previous cluster was observed.…”

Section: ) Description Of Clustersupporting

confidence: 53%

“…The remaining cases are no. 14 [51], 16 [53], 33 [70] and 34 [75]. Those have different application areas and neither fit in the smart city concept nor can build up a separate group.…”

Section: ) Description Of Clustermentioning

confidence: 99%

“…The next case study has a similar aim to the previous one. Here, the query performance of a library information system needed to be improved [53]. However, it has a different pattern of the fulfilled feature set, including only structured data from only one source.…”

Section: ) Description Of Clustermentioning

confidence: 99%

“…For instance, in case no. 16 [53], the main goal was to improve the query performance of a library information system. Within the given collection, this was the only case that solely handled structured data.…”

Section: Derived Standard Use Casesmentioning

confidence: 99%

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Identifying Similarities of Big Data Projects–A Use Case Driven Approach

et al. 2020

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Big data is considered as one of the most promising technological advancements in the last decades. Today it is used for a multitude of data intensive projects in various domains and also serves as the technical foundation for other recent trends in the computer science domain. However, the complexity of its implementation and utilization renders its adoption a sophisticated endeavor. For this reason, it is not surprising that potential users are often overwhelmed and tend to rely on existing guidelines and best practices to successfully realize and monitor their projects. A valuable source of knowledge are use case descriptions, of which a multitude exists, each of them with a varying information density. In this design science research endeavor, 43 use cases are identified by conducting a thorough literature review in combination with the application and adaption of a corresponding template for big data projects. By a subsequent categorization, which is performed by identifying and employing a hierarchical clustering algorithm, nine different standard use cases emerge, as the contribution's artifact. This provides decision-makers with an initial entry point, which can be utilized to shape their project ideas, not only by identifying the general meaningfulness of their potential big data project but also in terms of concrete implementation details.

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Section: ) Description Of Clustersupporting

confidence: 53%

“…The remaining cases are no. 14 [51], 16 [53], 33 [70] and 34 [75]. Those have different application areas and neither fit in the smart city concept nor can build up a separate group.…”

Section: ) Description Of Clustermentioning

confidence: 99%

Section: ) Description Of Clustermentioning

confidence: 99%

Section: Derived Standard Use Casesmentioning

confidence: 99%

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Identifying Similarities of Big Data Projects–A Use Case Driven Approach

et al. 2020

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“…When the applications are meant to be used only to handle certain amounts of data, a relational model database design is feasible to be used, but when the data to be processed is very large, complex and requires a dynamic schema change, the database that should be used is NoSQL. Applications like e-commerce, CMS and business applications are more optimal when developed with database schemes using NoSQL [1] [3]. Other examples of applications using complex and a lot of data are student academic application and library application.…”

Section: Introductionmentioning

confidence: 99%

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

Wahyuningrum

Sulastri

Sanjaya

2019

Journal of Information Systems

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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.

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Exploring the Potential of Big Data Analytics in Improving Library Management in Indonesia: Challenges, Opportunities, and Best Practice

Islam

Islam³

2023

Internet Reference Services Quarterly

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Enhancing query performance of library information systems using NoSQL DBMS: Case study on library information systems of Universitas Indonesia

Cited by 3 publications

References 5 publications

Identifying Similarities of Big Data Projects–A Use Case Driven Approach

Identifying Similarities of Big Data Projects–A Use Case Driven Approach

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

Exploring the Potential of Big Data Analytics in Improving Library Management in Indonesia: Challenges, Opportunities, and Best Practice

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