EDA and Tableau Analysis for Identification of Heart Disease Risk Factors

Heart disease is one of the leading causes of death worldwide, influenced by various risk factors such as high blood pressure, cholesterol levels, and lifestyle. This study analyzes the risk factors for heart disease using the Heart Disease Dataset which includes more than 1,000 records with variables such as age, blood pressure, cholesterol, and alcohol consumption. Exploratory Data Analysis (EDA) was applied to identify patterns and relationships between variables, while Tableau was used to present the results visually and interactively. The results showed that high blood pressure was the main risk factor, with the majority of patients having blood pressure in the range of 130-135 mmHg, which is considered high risk. In addition, high cholesterol levels (200-205 mg/dL) also contributed significantly to the increased risk of heart disease, while alcohol consumption in the "Heavy" category worsened heart health conditions. Data visualization shows an increasing trend in heart disease cases, especially in individuals with a combination of these risk factors. Therefore, this study emphasizes the importance of routine blood pressure and cholesterol monitoring, implementing a healthy diet, regular physical activity, and health education to reduce the incidence of heart disease in the future.

Authors

Institutions

Publication Details

Journal
Journal of Artificial Intelligence and Software Engineering (J-AISE)
Published
2025-03-26
DOI
https://doi.org/10.30811/jaise.v5i1.6389
Primary Topic
Technology and Data Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

EDA and Tableau Analysis for Identification of Heart Disease Risk Factors

Esi Putri Silmina, Legawan Perkasa
Journal of Artificial Intelligence and Software Engineering (J-AISE)
Technology and Data Analysis
article

EDA and Tableau Analysis for Identification of Heart Disease Risk Factors

Esi Putri Silmina, Legawan Perkasa
article en

Abstract

Heart disease is one of the leading causes of death worldwide, influenced by various risk factors such as high blood pressure, cholesterol levels, and lifestyle. This study analyzes the risk factors for heart disease using the Heart Disease Dataset which includes more than 1,000 records with variables such as age, blood pressure, cholesterol, and alcohol consumption. Exploratory Data Analysis (EDA) was applied to identify patterns and relationships between variables, while Tableau was used to present the results visually and interactively. The results showed that high blood pressure was the main risk factor, with the majority of patients having blood pressure in the range of 130-135 mmHg, which is considered high risk. In addition, high cholesterol levels (200-205 mg/dL) also contributed significantly to the increased risk of heart disease, while alcohol consumption in the "Heavy" category worsened heart health conditions. Data visualization shows an increasing trend in heart disease cases, especially in individuals with a combination of these risk factors. Therefore, this study emphasizes the importance of routine blood pressure and cholesterol monitoring, implementing a healthy diet, regular physical activity, and health education to reduce the incidence of heart disease in the future.

Journal of Artificial Intelligence and Software Engineering (J-AISE)Vol. 5(1)
Universitas 'Aisyiyah Yogyakarta
Openalex Percentile: Top 93%
Technology and Data Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

EDA and Tableau Analysis for Identification of Heart Disease Risk Factors — Esi Putri Silmina, Legawan Perkasa · Journal of Artificial Intelligence and Software Engineering (J-AISE) (2025) | TGRS Research Map | TGRS