Data Mining Integration with PostgreSQL Extension by K-Means, ID3 and 1R Method

Authors

  • Tri Wahyuningsih Magister Informatics Program, Universitas Raharja, Indonesia
  • I Ketut Gunawan Magister Informatics Program, Universitas Raharja, Indonesia
  • Abdullah Dwi Srenggini Magister Informatics Program, Universitas Raharja, Indonesia
  • Henry Riyandi Magister Informatics Program, Universitas Raharja, Indonesia

DOI:

https://doi.org/10.47738/ijiis.v5i2.129

Keywords:

Data Mining Techniques, Database Management System, Partition, Response time

Abstract

Data mining is a tool that allows users to quickly access large amounts of data. The purpose of this study was to analyze the integration of data mining technique algorithms into the PostgreSQL database management system. The method used in this research is K-Means, ID3 and 1R, the tools used to implement data mining using RapidMiner and PostgreSQL tools. In this study, the number of rows to be analyzed is 100,000 records, 500,000 records, and 1,000,000 records. The results obtained are the algorithm implemented to validate the data by using an experimental design that serves to observe the time that the analysis of the algorithm that has been integrated into the DBMS is smaller than the results from Rapidminer. As the number of records increases, data analysis becomes difficult using RapidMiner.Data mining techniques, Database management system, Partition, Response time

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Published

2022-03-21

Issue

Vol. 5 No. 2: March 2022

Section

Articles

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