Natural Language Interface to Database (NLIDB) for Decision Support Queries

Data access that is accurate, fast, and precise is a modern need for analysis or business decision making. NLIDB (Natural Language Interface to Database) is a system that allows users to access information from a database by entering requests that are stated in natural language. The NLIDB for Indonesian language that has been built has not been able to handle decision support data queries. The method of translating imperative sentences into SQL queries is done in two stages. The first stage is identifying the imperative sentence and parsing the sentence into a parsed tree that is assisted by the PC-PATR syntactic parser. The second stage is processing the parse tree into an SQL query. The parse tree is analyzed to look for parts of SQL, then do object searching for SQL parts to ontology. The objects found will be arranged into SQL queries. NLIDB application development is carried out to test the results of the translation of imperative sentences into SQL queries and see the application performance in translating imperative sentences into SQL queries. Application development is done with the Python programming language and MySQL database. The application that was built successfully translates imperative sentences into SQL queries for cross tab data, summary data, trend data, and top-N/bottom-N data. The application performance in carrying out the translation process is quite good, but it is necessary to improve performance for the ontology object searching process on the query generator component. Development that can be done for further research is the handling of sentence forms that have affixes and subquery handling.