Heart Failure Classification Using Support Vector Machine with Firefly Optimization

• Author(s): Khoirunnisa; Abiyyu Rasyiq Muhadzzib; Yazid Hilmi Allamsyah; Detty Purnamasari; Ulfa Hidayati
• Paper ID: 1718180
• Page: 3907-3913
• Published Date: 26-05-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 11 May-2026

Abstract

Heart failure remains a major global cause of death, making accurate mortality prediction crucial for effective clinical decision-making. This study proposes a mortality classification model using a Support Vector Machine (SVM) optimized with the Firefly Algorithm (FA). This approach overcomes the limitations of conventional machine learning methods that rely on manual hyperparameter tuning and frequently produce suboptimal performance when applied to complex clinical datasets. The dataset contains 299 heart failure patient records with 12 clinical attributes and one target label. Preprocessing steps include winsorizing for outlier, feature standardization, and handling class imbalance using the Synthetic Minority Oversampling Technique (SMOTE). FA is applied to automatically optimize the SVM hyperparameters, specifically cost (C) and gamma (γ), to improve classification performance. The proposed FA–SVM model achieved 90.24% test accuracy and a recall score of 0.93 for deceased patients, demonstrating strong capability in detecting high-risk cases. These results indicate that combining FA with SVM improves predictive accuracy and model stability, showing promise as a clinical decision support tool for early heart failure risk detection.

Keywords

Firefly Algorithm, Heart Failure Classification, Machine Learning, Support Vector Machine, FA-SVM

Citations

IRE Journals:
Khoirunnisa, Abiyyu Rasyiq Muhadzzib, Yazid Hilmi Allamsyah, Detty Purnamasari, Ulfa Hidayati "Heart Failure Classification Using Support Vector Machine with Firefly Optimization" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 3907-3913 https://doi.org/10.64388/IREV9I11-1718180

IEEE:
Khoirunnisa, Abiyyu Rasyiq Muhadzzib, Yazid Hilmi Allamsyah, Detty Purnamasari, Ulfa Hidayati "Heart Failure Classification Using Support Vector Machine with Firefly Optimization" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1718180