Pendekatan Hibrida Decision Tree-Particle Swarm Optimization untuk Deteksi Dini Penyakit Ginjal Kronis

Wina Widiati, Nandang Iriadi, Indah Ariyati, Imam Nawawi, Sugiono Sugiono

Abstract


Penelitian ini mengusulkan pendekatan hibrida yang menggabungkan Decision Tree (DT) dengan Particle Swarm Optimization (PSO) untuk deteksi dini Penyakit Ginjal Kronis (PGK). Kami mengidentifikasi permasalahan dalam akurasi yang kurang maksimal dalam prediksi PGK dengan menggunakan metode DT padahal metode DT dapat ditingkatkan, sehingga kami mengusulkan solusi dengan mengintegrasikan kejelasan interpretasi DT dan kemampuan optimasi PSO. Melalui analisis data klinis CKD, kami menunjukkan peningkatan signifikan dalam akurasi dan AUC dari 98.25% menjadi 98.50% dan 0.931 menjadi 0.984, masing-masing. Evaluasi menunjukkan peningkatan presisi dari 98.04% menjadi 98.71%. Pendekatan hibrida DT+PSO menawarkan kemungkinan aplikasi praktis dalam manajemen dan prognosis PGK, serta unggul dalam akurasi prediksi dan interpretasi model. Temuan ini memiliki implikasi penting dalam pemahaman dan penanganan PGK secara dini.

Keywords


Decision Tree; Particle Swarm Optimization; Pendekatan Hibrida; Penyakit Ginjal Kronis

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DOI: https://doi.org/10.26905/jasiek.v6i1.13006

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JASIEK(Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer)
Department of Electrical Engineering, Universitas Merdeka Malang


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