Dashboard Pre-Processing Data (DPD) as Data Analysis System with Technological Innovation to Perform Pre-Processing Quantitative Data

Authors

  • Mashuri Institut Teknologi Sepuluh Nopember
  • Albertus Eka Putra Haryanto Institut Teknologi Sepuluh Nopember
  • Yola Argatha Manik Institut Teknologi Sepuluh Nopember
  • Dinar Sukma Dewi Institut Teknologi Sepuluh Nopember
  • Tegar Primadana Putra Institut Teknologi Sepuluh Nopember

Keywords:

Outlier Data; Distribution of the Data; Pre-Processing Data; Missing Value

Abstract

In essence, data in real-life always needs to be pre-processed or better known as pre-processing data. Pre-processing Data is one of the early techniques for converting raw data from various sources into cleaner information that can be used for further analysis. There are three types of pre-processing data, missing values, checking outlier data, and identifying the types of distribution in the data. Currently, statistical software that offers to be used in pre-processing data analysis has been widely and is quite familiar. However, the user is often can not run the analysis quickly. Therefore, there is the idea to create and develop an application or dashboard that can be used to solve these problems. The application this at is offered and trying to be developed is called "DPD (Dashboard Pre-Processing Data)". This application serves as a tool to pre-process data quickly and efficiently. In addition, with this application, it’s expected that users can identify missing values, data outliers, and some types of data distribution, so users can determine the analysis method that will be used on the research data they have.

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Published

2025-09-02

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Section

Articles