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

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

Jurnal Publikasi Teknik Informatika (JUPTI)
Vol 2 No 2 (2023): Mei: Jurnal Publikasi Teknik Informatika

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.