Analisis Pola Temporal Volume Kendaraan di Kota Kediri Menggunakan LSTM
DOI:
https://doi.org/10.29407/k37e6z24Abstract
Pertumbuhan jumlah kendaraan di perkotaan memerlukan pemahaman yang baik terhadap pola temporal lalu lintas untuk mendukung pengelolaan transportasi. Penelitian ini bertujuan menganalisis pola temporal volume kendaraan di Kota Kediri menggunakan algoritma Long Short-Term Memory (LSTM). Data diperoleh dari enam titik CCTV Dinas Perhubungan Kota Kediri pada bulan Mei 2026 dengan deteksi kendaraan menggunakan algoritma YOLOv11. Tahapan meliputi preprocessing data, ekstraksi fitur temporal, pemodelan CNN-BiLSTM, dan evaluasi menggunakan MAE dan RMSE. Hasil evaluasi menunjukkan MAE sebesar 1,69 dan RMSE sebesar 2,30. Analisis pola menunjukkan puncak volume pada pukul 09.00 dengan rata-rata 5,76 kendaraan per frame dan lonjakan pada pukul 16.00. Terdapat perbedaan pola antara hari kerja dan akhir pekan. LSTM mampu mengidentifikasi pola temporal lalu lintas perkotaan secara efektif.
Keywords:
jam sibuk, lalu lintas, LSTM, pola temporal, time-series##plugins.themes.default.displayStats.downloads##
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