COMPARISON OF INDEX, PARTITION, AND MATERIALIZED VIEW METHODS ON THE ORACLE DATABASE STUDY ON CENTRAL GOVERNMENT FINANCIAL REPORTS (LKPP)

  • M Harviandi Rachman Faculty of Information Technology, Master of Computer Science Study Program, Universitas Budi Luhur, Indonesia
  • Samidi Faculty of Information Technology, Master of Computer Science Study Program, Universitas Budi Luhur, Indonesia
  • Eko Aprianto Faculty of Information Technology, Master of Computer Science Study Program, Universitas Budi Luhur, IndonesiaUniversitas Budi Luhur
Keywords: Indexing, Materialized View (MV), Performance optimization, Query optimization, Table partitioning

Abstract

The Indonesian Central Government Financial Report (LKPP) is a financial document prepared to increase transparency and accountability in the implementation of the State Revenue and Expenditure Budget (APBN). It is prepared within a tight schedule, hence changes made by each entity must be updated promptly. Therefore, this research focuses on the optimal table design for presenting financial reports. Query optimization is a major concern in database design, with the use of indexing concepts to increase data search speed. Table partitioning is also a strategy to consider, namely dividing a table into parts that form separate data ranges. The use of a Materialized View (MV) is another alternative, providing increased performance with the space-for-time trade-off principle. Experiments were carried out by comparing the response time of applying index, partition, and materialized views to produce financial report data. Experimental results indicate that materialized views can provide significant advantages when faced with large volumetric data. The decision to choose a materialized view can be considered contextually, depending on the specific needs and characteristics of the data encountered in a database system.

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Published
2024-07-24
How to Cite
[1]
M. H. Rachman, S. Samidi, and E. Aprianto, “COMPARISON OF INDEX, PARTITION, AND MATERIALIZED VIEW METHODS ON THE ORACLE DATABASE STUDY ON CENTRAL GOVERNMENT FINANCIAL REPORTS (LKPP)”, J. Tek. Inform. (JUTIF), vol. 5, no. 4, pp. 1009-1014, Jul. 2024.