Atrition Analysis using XG Boost and Support Vector Machine Algorithms


Authors : Bandung Prihanto; Catherine Olivia Sereati; Maria A. Kartawidjaja; Marsul Siregar

Volume/Issue : Volume 8 - 2023, Issue 6 - June

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://tinyurl.com/zt5dx4zw

DOI : https://doi.org/10.5281/zenodo.8126484

Abstract : The presence of the internet network which is getting faster and the digital world which is growing rapidly in various fields have a very big influence on every aspect of human life, not limited to people who are related, especially jobs in the field of information technology but also outside the field of information technology. The massive development of the digital ecosystem and the entry of the industrial era 4.0 means that more and more data is available on the internet. A large amount of data available then raises various problems in terms of how to process and analyze data so that this data can be useful in human life both within the scope of individuals or companies and in the fields of education, health and so on. With the concept of Machine Learning technology, problems in processing and analyzing large amounts of data can be solved more quickly when compared to doing it manually by humans. The more data that is processed, the performance of Machine Learning in conducting analysis will increase. In this analysis process, the determined algorithm also affects the performance of Machine Learning. The Author will use Google's services in this research, namely Google Colaboratory. Then the Author will also compare the use of two algorithms, XG Boost, and Support Vector Machine, as well as carry out the feature selection process.

Keywords : Machine learning, pearson, xg boost, support vector machine, employee turnover.

The presence of the internet network which is getting faster and the digital world which is growing rapidly in various fields have a very big influence on every aspect of human life, not limited to people who are related, especially jobs in the field of information technology but also outside the field of information technology. The massive development of the digital ecosystem and the entry of the industrial era 4.0 means that more and more data is available on the internet. A large amount of data available then raises various problems in terms of how to process and analyze data so that this data can be useful in human life both within the scope of individuals or companies and in the fields of education, health and so on. With the concept of Machine Learning technology, problems in processing and analyzing large amounts of data can be solved more quickly when compared to doing it manually by humans. The more data that is processed, the performance of Machine Learning in conducting analysis will increase. In this analysis process, the determined algorithm also affects the performance of Machine Learning. The Author will use Google's services in this research, namely Google Colaboratory. Then the Author will also compare the use of two algorithms, XG Boost, and Support Vector Machine, as well as carry out the feature selection process.

Keywords : Machine learning, pearson, xg boost, support vector machine, employee turnover.

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe