1. Analyzing Database Optimization Strategies in Laravel for an Enhanced Learning Management.
- Author
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Sasmoko, Indrianti, Yasinta, Manalu, Sonya Rapinta, and Danaristo, Jevon
- Subjects
DATABASES ,LEARNING Management System ,BIG data ,DOCUMENTATION ,ALGORITHMS - Abstract
Database performance is a measure of the time taken for a process to request and retrieve data from a database. The performance can vary depending on the implementation environment, algorithm, and the scale of data. One instance of the implementation is through a web system in the form of a Learning management system (LMS). LMS is a digitalized learning media with one of the critical components being a database system. The performance of the database system will affect the quality of the LMS activity of administration, documentation, tracking, reporting, and delivery of educational content. The importance of database performance creates the need to evaluate the database performance in an LMS environment. This study aims to assess the query performance of three query methods of implementation in Laravel: raw query, object-relational mapper (ORM), and query builder in an LMS environment. The method was then evaluated along with optimization practices, such as removing the leading wildcard and indexing. This study is dedicated to the optimization, speed comparison, and requirements for query optimization in Laravel. The study concludes that optimization through indexing with the B-tree algorithm contributes to faster query time in big data despite falling behind for queries with leading wildcards. The hash algorithm, on the other side, shows consistent improvement with the leading wildcard but with less significant improvement. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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