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All Journal Jurnal Komputer Terapan
Zarkasi, Mohamad
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Computer Science & IT

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Analisi Data Eksploratori Kritis untuk Dataset Prediksi Stroke Ariful Furqon, Muhammad Arif; Najwa, Nina Fadilah; Zarkasi, Mohamad; Pandunata, Priza; Fajariyanto, Gama Wisnu
Jurnal Komputer Terapan Vol 10 No 1 (2024): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v10i1.6307

Abstract

Stroke is a significant global health concern, requiring an in-depth understanding of the complex factors contributing to its occurrence. Age, body mass index (BMI), and average glucose levels are critical factors in stroke etiology. This study employed exploratory data analysis techniques to investigate the relationships between variables in a stroke prediction dataset. The research methodology included (1) dataset description, (2) data preprocessing, (3) exploratory data analysis, and (4) interpretation. Descriptive statistical analysis provided insights into the dataset's composition and variability, while data preprocessing techniques handled missing values and facilitated feature extraction. Based on exploratory data analysis, significant relationships were found between age, hypertension, heart disease, average glucose levels, and stroke. However, BMI showed a less significant role in stroke. These findings contribute to a better understanding of the factors contributing to stroke risk and may aid in developing more effective prevention strategies.
Co-Authors Ariful Furqon, Muhammad Arif Fajariyanto, Gama Wisnu Najwa, Nina Fadilah Priza Pandunata