Model Otomatisasi Cerdas Berbasis data Spasial untuk Prioritas Perbaikan Jalan Rusak
DOI:
https://doi.org/10.33795/jip.v12i1.8654Keywords:
kerusakan jalan, Sistem Informasi Geografis, Random Forest, sistem rekomendasiAbstract
Kerusakan jalan berdampak signifikan terhadap keselamatan dan efisiensi sosial-ekonomi. Pendekatan manual dalam menentukan prioritas perbaikan seringkali tidak akurat, terutama di wilayah dengan karakteristik spasial kompleks seperti Kabupaten Pasuruan. Penelitian ini mengusulkan sistem rekomendasi cerdas berbasis data spasial menggunakan model hybrid, yang mengintegrasikan metode Simple Additive Weighting (SAW) untuk perankingan dan Random Forest (RF) untuk validasi klasifikasi. Dataset mencakup 100 segmen jalan dengan atribut spasial dan non-spasial. SAW berhasil mengklasifikasikan segmen ke dalam tiga kelas prioritas dengan tingkat konsistensi 92%, yang didukung oleh hasil RF. Model RF juga menunjukkan kinerja baik dengan precision, recall, dan F1-score rata-rata sebesar 0,87, serta mampu mengidentifikasi fitur penting. Integrasi SAW-RF dalam kerangka GIS terbukti efektif meningkatkan efisiensi dan transparansi. Prototipe ini berpotensi untuk direplikasi di daerah lain menggunakan platform open source
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