Automated Data Integration, Cleaning and Analysis Using Data Mining and SPSS Tool For Technical School in Malaysia

TL;DR

This paper presents an automated data mining system using SPSS to integrate, clean, and analyze educational data, enabling faster and more accurate decision-making for technical schools in Malaysia.

Contribution

It introduces an automated data mining approach for educational data analysis that matches manual results but offers improved efficiency and decision support.

Findings

Automated system produces results consistent with manual analysis.

System enables faster decision-making for educational management.

Improves data processing efficiency in educational settings.

Abstract

This study aims to integrate, clean and analysis through automated data mining techniques. Using data mining (DM) techniques is one of the processes of transferring raw data from current educational system to meaningful information that can be used to help the school community to make a right decision to achieve much better results. This proved DM provides means to assist both educators and students, and improve the quality of education. The result and findings in the study show that automated system will give the same result compare with manual system of integration and analysis and also could be used by the management to make faster and more efficient decision in order to map or plan efficient teaching approach for students in the future.