基于输入命令句的MySQL命令语法生成

B. Indriyono, Zudha Pratama
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引用次数: 1

摘要

信息检索系统是一种广泛应用于信息检索的系统。本研究将讨论系统如何查找存储在数据库表中的信息。数据库中的表被安排用来存储数据库用户输入的所有形式的数据,以便以后可以再次使用存储的数据。重新访问数据库的信息必须通过一种称为数据库管理系统(DBMS)的机制。最广泛使用的DBMS之一是MySQL。通过使用DBMS,可以根据用户的需要对信息和数据进行操作。数据库中的数据操作是用一种特殊的语言完成的,即SQL(结构查询语言)。掌握SQL命令是数据库用户的义务,这样被操纵的数据才能产生所需的信息。但是,许多数据库用户仍然不理解实际的SQL命令语法是如何管理数据并将其操作为信息的。当然,如果不立即寻求解决方案,这是非常危险的,因为它将阻碍从数据库中存储的数据检索信息的过程。为了解决这个问题,有必要设计一个系统,帮助数据库用户将他们的愿望转换成SQL命令语法。本文将讨论如何将印尼语中的命令翻译成SQL命令语法。解决这一研究问题的方法是基于规则的。主要过程有两个阶段:预处理阶段,包括单词标记化过程;翻译阶段,包括关键字分组过程。关键字分组过程包括关键字组分析阶段、表列分析阶段、SQL命令识别阶段和SQL命令映射阶段。从已经通过的所有阶段和7个场景的测试来看,每个场景有10个命令,准确率为81.42%。测试过程中的不准确性更多的是显示来自两个或更多表的数据的问题,例如,使用join表命令。这个问题可以通过为表连接的使用添加新规则来解决。
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Generating SQL Command Syntax Using MySQL Based on Typing Command Sentence
Information retrieval system is a system that is widely used to retrieve information. This research will discuss how the system finds back the information stored in database tables. Tables in the database are arranged to store all forms of data entered by database users so that later the stored data can be used again. Re-accessing the database's information must go through a mechanism known as a database management system (DBMS). One of the most widely used DBMS is MySQL. By using a DBMS, information and data can be manipulated according to user needs. Data manipulation in the database is done in a special language, namely SQL (Structure Query Language). Mastery of SQL commands is an obligation for database users so that the manipulated data can produce the required information. However, many database users still do not understand how the actual SQL command syntax manages and manipulates data into information. This is, of course, very risky if the solution is not immediately sought because it will hinder the process of retrieving information from the data stored in the database. For this problem to be resolved, it is necessary to design a system that can help database users translate their wishes into SQL command syntax. This paper will discuss how a command in Indonesian can be translated into SQL command syntax. The method used to solve this research problem is rule-based. There are two stages in the main process: the pre-processing stage, which consists of a word tokenization process, and a translation stage, including a keyword grouping process. This keyword grouping process consists of the keyword group analysis phase, table and column analysis, identification of SQL commands, and mapping of SQL commands. From all stages that have been passed and testing of 7 scenarios with ten (10) commands for each scenario, the accuracy is 81.42%. The inaccuracy in the testing process is more a problem of displaying data from two or more tables, for example, using the join table command. This problem can be addressed by adding new rules for the use of table joins.
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