Sartje Mala Rangkoly
Universitas AMIKOM Yogyakarta

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Analisis Perbandingan Performansi Waktu Respons Kueri antara MySQL PHP 7.2.27 dan NoSQL MongoDB Olivia Maria Inacio Tavares; Sartje Mala Rangkoly; Sarah Bunda Desy Bawan; Ema Utami; Muhammad Syukri Mustafa
(JurTI) Jurnal Teknologi Informasi Vol 4, No 2 (2020): DESEMBER 2020
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v4i2.1695

Abstract

Abstract – Currently now, every function of the governmental and private agencies are required to manage the system work properly, effectively, and certainly efficient in terms of both time and system flexibility. Not a few have used the use of basic management data to help maximize the work system that is being run. This research will be carried out by examining the performance when answering queries between 2 commonly used management database systems, namely the My Structured Query Language (MySQL) relational database and Not-Only SQL (NoSQL) MongoDB non-relational database tested on the Aspiration and Information Service System of Oebufu Village (SELMA) with the number of data records (50, 100, 500, 1000, 5000, 10000, 100000). The examiner is carried out on the Data Manipulation Language (DML) query, which is inserting, update, delete, and select functions in adding, modifying, and displaying data in the database. Testing is also carried out on the agreement function, namely Counting (COUNT), Total in 1 table (SUM), Average (AVG )functions as well as the AND OR liaison operator as well as testing data import and export. The research aims to provide the results of a performance comparison analysis between MySQL and MongoDB NoSQL query respond database to find out which one is more good for use. The results can be proven that the two databases have different speeds in response performance comparisons in each model test, where NoSQL MongoDB is proven to be superior in every transaction tested model, starting from DML queries and function aggregate testing, import-export of data tables, and intermediate operator function, but weak in comparing select queries to display data with a runtime difference of 1.95.Keywords: Database, Query Respond Time, MySQL, NoSQL, MongoDB. Abstrak - Saat ini, setiap fungsi kerja instansi kepemerintahan maupun swasta dituntut untuk dapat mengelola sistem kerja secara tepat, efektif dan tentunya efisien baik dari segi waktu maupun flexibilitas sistem. Tidak sedikit yang telah menggunakan pemanfaatan manajemen basis data dalam membantu memaksimalkan sistem kerja yang tengah dijalankan. Penelitian ini akan dilakukan pengujian kinerja waktu respond query diantara 2 sistem manajemen basis data yang telah umum digunakan yaitu database relasional My Structured Query Language (MySQL) dan database non-relasional Not-Only SQL (NoSQL) MongoDB yang diujikan pada Sistem Layanan Aspirasi dan Informasi Kelurahan Oebufu (SELMA) dengan banyak record data (50, 100, 500, 1000, 5000, 10000, 100000). Adapun pengujian dilakukan pada query Data Manipulation Language (DML) yaitu pada fungsi insert, update, delete dan select dalam menambah, mengubah, menghapus serta menampilkan data pada database. Pengujian juga dilakukan terhadap agregat fuction yaitu pada fungsi Counting (COUNT), Total dalam 1 tabel (SUM), Average (AVG) juga pada operator penghubung AND OR serta pengujian import dan export data. Penelitian bertujuan memberikan hasil analisis perbandingan kinerja waktu respond query diantara MySQL dan NoSQL MongoDB untuk mengetahui basis data mana yang lebih unggul untuk digunakan. Hasilnya dapat dibuktikan bahwa kedua database tersebut memiliki kecepatan waktu yang berbeda dalam perbandingan kinerja respon kueri pada setiap model pengujian, dimana NoSQL MongoDB terbukti lebih unggul, mulai dari pengujian query DML, pengujian agregat fuction, impor-export data serta fungsi operator penghubung, namun lemah dalam pemrosesan query select untuk menampilkan data dengan jumlah selisih waktu respon 1,95s.Kata kunci: Basis Data, Query Respond Time, MySQL, NoSQL, MongoDB
ANALISIS MODEL RESTRUKTURISASI KUERI DALAM MENGOPTIMASI WAKTU RESPONS EKSEKUSI DATA PADA BASIS DATA RELASIONAL MYSQL PHP 7.2.27 Olivia Maria Inacio Tavares; Sartje Mala Rangkoly; Sarah Bunda Desi Bawan; Khifni Beyk Ahmad; Ema Utami; Muhammad Syukri Mustafa
J-Icon : Jurnal Komputer dan Informatika Vol 9 No 1 (2021): Maret 2021
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v9i1.3598

Abstract

Database is a collection of data that forming an information that useful for managers in an organization to facilitate data management process to become more effective and safely guarantee. A good database has fast and accurate response time performance in data execution processing. To manage the database, it requires a special language or query known as Structure Query Language (SQL). Increase need for fast information, will need a proper SQL as well. Therefore, through this research, a test analysis will be used to optimize the query response time in database management system commonly used today, namely the My Structured Query Language (MySQL) using PHP version of 7.2.27 relational database which will be tested on the Oebufu Village Aspiration and Information Service System (SELMA) that acessed from localhost panels with a total of 1000 test data records. The test is devoted to the effectiveness of using SELECT queries in calling and displaying data through restructuring the use of clauses. This study aims to help improve data management by providing the results of the comparative analysis of response times between the general query model and the optimized query results in order to determine the correct and efficient query structure. The result is proven by doing query optimization, it is found that the presentation of time optimization is significant, which is 78% much faster than the initial query, through this test it can be concluded that optimization plays an important role in streamlining the response time of database queries.