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Tuning Database Pada Sistem Penerimaan Mahasiswa Baru Menggunakan Optimasi Query dan Indexing

Authors: Amat Deska; Ipal Akbar; - Samidi;

Tuning Database Pada Sistem Penerimaan Mahasiswa Baru Menggunakan Optimasi Query dan Indexing

Abstract

Dalam pengoperasian database MaraiaDB diperlukan aplikasi berupa server localhost yang memiliki response waktu untuk menjalankan sebuah query agar dapat mendapatkan waktu yang efisiensi. Pada penelitian ini mengukur perfoma query dalam bentuk SELECT pada database MariaDB yang sudah di install pada komputer atau laptop dengan menggunakan aplikasi yang bernama Xammp dengan jumlah record data kurang lebih sebanyak 12.000 data, tapi pada penelitian ini hanya memakai sekitar 5000 data. Data tersebut nantinya akan dilakukan optimasi query dan indexing. Permasalahan yang terjadi adalah lamanya proses pengambilan data yang membutuhkan waktu sehingga membutuhkan suatu cara agar dapat mempercepat proses pengambilan data. Metode optimasi database yang difokuskan pada pengujian ini adalah dengan melakukan perbandingan dari berbagai efektivitas sub query serta penggunaan indexing pada tabel. Pada Query yang diuji adalah fungsi yang bernama LEFT JOIN, WHERE, ON, GROUP BY, ORDER BY dan DML (Data Manipulation Language), yaitu QUERY SELECT yang akan di lakukan pada aplikasi Xammp. Pada penelitian ini hasil yang di harapkan berupa pengambilan data yang akan menjadi lebih cepat atau efisien untuk meningkatkan kinerja pada database setelah melakukan Optimasi SQL Query dan Table Indexing.

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Keywords

index, tuning, optimasi database, Information technology, sql query, T58.5-58.64

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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