NL2SQL For Chatbot with Semantic Parsing Using Rule-Based Methods

Abstract

Structured Query Language (SQL) is a command language that allows users to access database information. Ordinary people generally donot know how to make queries with SQL to a database. The chatbot is acomputer program developed to interact with its users via text or voice. In this study, chatbots were developed to help and facilitate users intheNatural Language to Structured Query Language (NL2SQL) process tosearch for information in an Academic Information Systemdatabasewith semantic parsing using a rule-based method that accepts input inthe form of interrogative sentences or order. In the Natural Language toStructured Query Language (NL2SQL) process several problems arise, namely input problems with unique parameters for the knowledge base, and slow searching or translation processes, which make Natural Language to Structured Query Language (NL2SQL) inef icient, problems This problem will be solved using a semantic parsingapproach using a rule-based method that is proven to be ef icient insolving issues such as the Natural Language to Structured QueryLanguage (NL2SQL) process. The results showed that the semanticparsing approach using the rule-based method succeeded in obtainingan accuracy rate of 96.72% using 122 test data in the formof questionsentences or command data about the Academic Information Systemof the Department of Informatics Engineering, Sriwijaya University inIndonesian, and an average execution time of 50.68 milliseconds. seconds or 0.05 seconds.