Bioinformatics Database Query Performance and Optimization
Edy Budiman1, Andi Tejawati2, Ummul Hairah3
1Edy Budiman*, Informatics Department, Universitas Mulawarman, Samarinda, Indonesia.
2Andi Tejawati, Informatics Department, Universitas Mulawarman, Samarinda, Indonesia.
3Ummul Hairah, Informatics Department, Universitas Mulawarman, Samarinda, Indonesia.
Manuscript received on August 01, 2020. | Revised Manuscript received on August 05, 2020. | Manuscript published on September 30, 2020. | PP: 581-588 | Volume-9 Issue-3, September 2020. | Retrieval Number: 100.1/ijrte.C4666099320 | DOI: 10.35940/ijrte.C4666.099320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Borneo bioinformatics portal test is a critical element of SQA and represents a comprehensive review of specifications, design and coding. The test represents an abnormality in the development of the portal. A series of tests systematically reveals several different types of errors. This study aims to evaluate the performance and optimization of Borneo’s Bioinformatics portal with a series test activities using the Web Performance Optimization methodology. Testing query performance with measuring the response time and page loading timings from the object relationship mapping (ORM) model Laravel PHP framework in offline and online. For optimization, we set a pre-test and post-test scenario to evaluate the efficiency performance test results. The results study found that the query relation model, parsing script (javaScript and CSS), service scale and dimension images in the interaction process to the database are the dominant resources affecting the performance of the Bioinformatics portal. Performance optimization through determining the appropriate query relation model, minify and defer parsing script or combine images using CSS sprites to reduce scala image.
Keywords: Bioinformatics, query, database relationship, ORM.