PREDIKSI PEMANENAN ENERGI PADA ARRAY PIEZOELEKTRIK KONFIGURASI SERI-PARALEL BERBASIS RANDOM FOREST REGRESSION
DOI:
https://doi.org/10.36257/teliska.v19iI.11829Kata Kunci:
Random Forest Regression, Pemanenan Energi, Piezoelektrik, Smart Carpet, Konfigurasi Seri-ParalelAbstrak
Penelitian ini menganalisis karakteristik elektrik dan memprediksi luaran daya sistem piezoelectric smart carpet melalui komparasi konfigurasi rangkaian seri dan paralel menggunakan algoritma Random Forest Regression (RFR). Sistem dirancang menggunakan 16 elemen keramik piezoelektrik per blok yang diintegrasikan ke dalam struktur karpet sepanjang 100 cm. Data eksperimental dikumpulkan dari lima subjek dengan massa tubuh 54–98 kg melalui aktivitas jalan dan lari, menghasilkan 100 sampel observasi. Hasil pengujian menunjukkan konfigurasi seri menghasilkan rata-rata daya 1649.3 mW, melampaui konfigurasi paralel sebesar 104.8% yang hanya menghasilkan 805.1 mW, dengan tegangan puncak mencapai 80 V pada aktivitas lari. Model RFR yang dioptimasi menggunakan GridSearchCV dengan 5-fold cross-validation mencapai koefisien determinasi () sebesar 88.25%, Mean Absolute Error (MAE) 145.06 mW, dan Root Mean Squared Error (RMSE) 179.15 mW. Analisis feature importance mengungkapkan bahwa konfigurasi rangkaian (47.59%) dan frekuensi langkah (47.18%) merupakan faktor dominan, sementara massa tubuh hanya berkontribusi 5.22% akibat saturasi mekanik pada struktur karpet. Penelitian ini membuktikan RFR efektif sebagai model prediktif untuk optimasi sistem pemanenan energi biomekanik pada infrastruktur publik.
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