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Big data implementation in Tesla using classification with rapid miner

delete2021-01-01
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PRE
AI
A
Andry, Johanes Fernandes
G
Gunadi, Julia
R
Rembulan, Glisina Dwinoor
T
Tannady, Hendy *
DOI：10.22075/ijnaa.2021.6016delete
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Abstract

Abstract

En 中文
In this study, we will analyze how big data is implemented in TESLA Company, in this case, we will use sales data. With the growing of big data and the need for its use in the 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. For 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 result are from 2621300 to 18766300.
Keywords:
Big data
Classification
Data
TESLA

Journal

I
International Journal of Nonlinear Analysis and Applications
IF:
0
Papers:
8
Citations:
0

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No organization information available