Pemeliharaan Prediktif Berbasis ANFIS untuk Perangkat EKG Portabel Menggunakan Masukan Multi-Sensor

Agus Supriyanto; Arief Marwanto

doi:10.59485/yj0ty525

Penulis

Agus Supriyanto Universitas Islam Sultan Agung
Arief Marwanto Universitas Islam Sultan Agung

DOI:

https://doi.org/10.59485/yj0ty525

Kata Kunci:

ANFIS, predictive maintenance, ECG portabel, multi-sensor

Abstrak

Perkembangan peralatan medis portabel seperti Electrocardiograph (ECG) di Rumah Sakit tipe C menghadapi tantangan signifikan dalam hal pemeliharaan preventif akibat keterbatasan data historis dan ketidakmampuan metode konvensional dalam memodelkan hubungan non-linear antara parameter operasional dengan risiko kegagalan. Penelitian ini mengusulkan kerangka kerja predictive maintenance berbasis Adaptive Neuro-Fuzzy Inference System (ANFIS) dengan integrasi multi-sensor yang mencakup suhu, kelembaban, durasi pemakaian, dan umur alat. Data sintetis berjumlah 230 sampel (30 historis + 200 sintetis) dihasilkan menggunakan fungsi keanggotaan sigmoid untuk mengatasi kelangkaan data. Model ANFIS dilatih dengan arsitektur 5 lapisan menggunakan fungsi keanggotaan generalized bell dan algoritma hibrida backpropagation serta least squares. Hasil evaluasi menunjukkan akurasi model mencapai 98,67% pada data uji, dengan presisi 92,3%, recall 98,2%, dan F1-score 95,2%. Perbandingan dengan metode Fuzzy Mamdani (96,67%), Random Forest (91,5%), dan SVM (88,3%) menunjukkan keunggulan signifikan ANFIS dalam menangani kompleksitas data multi-variabel. Nilai AUC sebesar 0,978 mengonfirmasi kemampuan diskriminasi model yang sangat baik. Kerangka kerja ini berkontribusi pada pengembangan sistem prediktif yang adaptif, akurat, dan interpretabel untuk manajemen peralatan medis di fasilitas kesehatan dengan sumber daya terbatas.

Unduhan

Data unduhan tidak tersedia.

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