Pelacakan Kerumunan Adaptif: Deteksi Cerdas Berdasarkan Pergerakan Pengunjung Di Area Wisata Menggunakan Yolo
Abstract
Pertumbuhan jumlah pengunjung di kawasan wisata terbuka seperti Kawah Putih mendorong perlunya sistem pemantauan keramaian yang akurat dan efisien untuk mendukung pengambilan keputusan pengelola dalam menjaga kenyamanan dan keamanan pengunjung. Penelitian ini mengembangkan sistem deteksi dan penghitung keramaian berbasis pergerakan (movement counter) secara real-time menggunakan algoritma YOLOv8 untuk deteksi objek dan centroid tracker untuk pelacakan arah gerak. Sistem ini mampu membedakan pergerakan masuk dan keluar pengunjung dengan memanfaatkan metode pendeteksian garis lintas (line crossing). Hasil deteksi diintegrasikan dengan platform web menggunakan framework Flask, sehingga data jumlah pengunjung dapat ditampilkan secara real-time dalam bentuk grafik dan tabel. Pengujian dilakukan pada lokasi dengan tingkat keramaian tinggi. Hasil menunjukkan bahwa sistem mampu mendeteksi pergerakan individu secara akurat, dengan performa yang stabil di berbagai kondisi lingkungan. Penelitian ini membuktikan bahwa sistem crowd monitoring berbasis AI dan computer vision dapat diimplementasikan secara efektif untuk mendukung pengelolaan destinasi wisata secara modern dan non-invasif.
Kata kunci— pendeteksi keramaian, penghitung pergerakan, YOLOv8, centroid tracker, monitoring real-time, area wisata.
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