Big data implementation in Tesla using classification with rapid miner

Document Type : Research Paper


1 Information Systems Department, Universitas Bunda Mulia, Jakarta, Indonesia

2 Industrial Engineering Department, Universitas Bunda Mulia, Jakarta, Indonesia

3 Management Department, Kalbis Institute, Jakarta, Indonesia


In this study, we will analyze how big data is implemented in TESLA Company, in this case, we will use sales data. With the growth of big data and the need for its use in companies, nowadays big data is everywhere. TESLA is an American automobile and energy storage company founded by engineers Martin Eberhard and Marc Tarpenning in July 2003 under the name Tesla Motors. The company name is a tribute to inventor and electrical engineer Nikola Tesla. Eberhard said that he wanted to build an automobile manufacturer and also a technology company whose core technology is batteries, computer software and proprietary electric motors. As the amount of data that companies must process today continues to increase, companies must keep up with the times by using big data. Big data can be used to move, contain, and access large amounts of unstructured and disparate data in a timely manner. it is good. The method we use is quantitative data. This calculation will use the Rapid Miner software. The result of this study is the data is 2,146 units, total volume from 118,500 to 47,065,000 based on the number of existing sales, and classification results are from 2621300 to 18766300.


Volume 12, Special Issue
January 2021
Pages 2057-2066
  • Receive Date: 04 September 2022
  • Revise Date: 04 October 2022
  • Accept Date: 04 November 2022
  • First Publish Date: 04 November 2022