Prediksi Kejadian Fibrilasi Atrium Paroksismal Menggunakan Jaringan Syaraf Tiruan dan Particle Swarm Optimization dengan Fitur Interval RR

Fahmi Alhafid, Nuryani Nuryani, Darmanto Darmanto

Abstract

Fibrilasi Atrium (FA) merupakan jenis aritmia yang paling umum dengan peningkatan resiko 1,5 hingga 2 kali lipat dari semua penyebab kematian dan peningkatan morbiditas. FA Paroksismal (FAP) adalah salah satu tipe fibrilasi atrium. Studi mengenai FAP menunjukkan bahwa 20% - 30% individu dengan FA memiliki FAP. Penelitian untuk membuat model predictor tool FAP menggunakan Jaringan Syaraf Tiruan (JST) telah dilakukan. Fitur Statistik interval RR dijadikan fitur masukan pada JST Radial Basis Function (RBF) dengan optimasi menggunakan Particle Swarm Optimization (PSO). Data Elektrokardiogram (EKG) yang digunakan adalah Atrial Fibrillation Prediction Database (AFPDB) dari PyhsioNet. Dengan target keluaran JST berupa PAF dan normal. Parameter RBF yang dioptimasi dengan PSO meliputi pusat, lebar dan bobot. Hasil fitur tunggal diperoleh bahwa sistem JST PSO-RBF lebih baik jika dibandingkan dengan JST RBF dalam membuat model predictor tool FAP. Dengan variasi fitur statisitik diperoleh sistem prediksi FAP dengan akurasi, sensitivitas dan spesifitas secara berturut-turut bernilai 85,82%, 84,15% dan 87,78%.

Keywords

FA Paroksismal; RBF; PSO-RBF

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References

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DOI: https://doi.org/10.13057/ijap.v10i01.39746

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