Implementasi Bahasa Python Dalam Menganalisis Pengaruh Rokok Terhadap Risiko Pasien Terkena Penyakit Stroke

Authors

  • Kairos Abinaya Susanto Universitas Bina Nusantara
  • Darrien Rafael Wijaya Universitas Bina Nusantara
  • Matthew Owen Universitas Bina Nusantara
  • Tertius Raya Prasetya Universitas Bina Nusantara
  • George Maximillian Theodore Universitas Bina Nusantara
  • Jevant Russell Universitas Bina Nusantara
  • Rahmi Yulia Ningsih Universitas Bina Nusantara

DOI:

https://doi.org/10.55606/jupti.v2i2.1722

Keywords:

Python, Smoking, Statistics, Stroke

Abstract

This study discusses the implementation of Python programming language in analyzing the influence of smoking habits on the risk of stroke in patients. The study utilizes the "Stroke Prediction Dataset" from World Health Organization (WHO) as the research data source. By employing exploratory data analysis methods, the study can model statistics, visualize data, and test hypotheses to gather supporting variables in analyzing the impact of smoking on the risk of stroke. The analysis results indicate that smoking significantly contributes to an increased risk of stroke. The relationship between smoking status and stroke risk is also influenced by other factors such as age, gender, and other underlying health conditions like hypertension and heart disease.

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Published

2023-05-31

How to Cite

Kairos Abinaya Susanto, Darrien Rafael Wijaya, Matthew Owen, Tertius Raya Prasetya, George Maximillian Theodore, Jevant Russell, & Rahmi Yulia Ningsih. (2023). Implementasi Bahasa Python Dalam Menganalisis Pengaruh Rokok Terhadap Risiko Pasien Terkena Penyakit Stroke. Jurnal Publikasi Teknik Informatika, 2(2), 48–58. https://doi.org/10.55606/jupti.v2i2.1722