JEMBATAN BERKELANJUTAN: PERSPEKTIF FILSAFAT ILMU MELALUI INTEGRASI PEMANTAUAN KESEHATAN STRUKTUR DAN ANALISIS BIAYA SIKLUS HIDUP BERBASIS JARINGAN SYARAF TIRUAN
Abstract
Jembatan merupakan aset infrastruktur kritis yang memastikan kelangsungan dan efisiensi jaringan transportasi. Namun, keberlanjutan jangka panjangnya tetap menjadi masalah mendesak akibat penuaan, kerusakan, dan biaya pemeliharaan serta rehabilitasi yang terus meningkat. Studi ini mengeksplorasi integrasi pemantauan kesehatan struktural (Structural Health Monitoring (SHM)) dan analisis biaya siklus hidup (Life Cycle Cost Analysis (LCCA)) berbasis jaringan saraf tiruan (Artificial Neural Network (ANN)) sebagai pendekatan inovatif untuk meningkatkan keberlanjutan jembatan. Berlandaskan filosofi ilmu pengetahuan, penelitian ini menganalisis bagaimana integrasi ini dapat merevolusi manajemen jembatan dengan memfasilitasi pengambilan keputusan berbasis data dan mengoptimalkan alokasi sumber daya. Metodologi penelitian meliputi tinjauan literatur komprehensif, pengembangan kerangka konseptual, dan studi kasus yang menunjukkan penerapan praktis pendekatan yang diusulkan. Temuan utama menyoroti potensi SHM dan LCCA berbasis ANN dalam memberikan wawasan real-time tentang kinerja jembatan, memprediksi degradasi di masa depan, dan mengidentifikasi strategi pemeliharaan yang efisien secara biaya. Studi ini menyimpulkan bahwa integrasi ini selaras dengan prinsip-prinsip ilmu keberlanjutan dan menawarkan jalur yang menjanjikan menuju infrastruktur jembatan yang lebih tangguh, ekonomis, dan ramah lingkungan.
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