Penerapan Metode XGBoost Untuk Memprediksi Jumlah Kejadian Kecelakaan Lalu Lintas di Kota Banjarmasin
DOI:
https://doi.org/10.29407/gj.v7i1.19807Keywords:
rainfall, traffic accident, prediction, xgboostAbstract
Setiap tahunnya terjadi kecelakaan lalu lintas seperti yang tercatat pada data dari Polisi sejak tahun 2016 sampai dengan 2020 yang ditambah dengan data dari sosial media pada tahun 2021 sampai bulan Oktober. Selain berdasarkan data kecelakaan lalu lintas terdapat juga hal yang dapat mempengaruhi terjadinya kecelakaan seperti curah hujan. Berdasarkan permasalahan tersebut, penelitian ini akan melakukan prediksi terhadap jumlah kejadian kecelakaan lalu lintas yang akan terjadi di kota Banjarmasin menggunakan metode XGBoost. Data yang telah dikumpulkan akan diolah dalam rentang waktu bulanan serta pengujian model menggunakan dua metode yaitu RMSE untuk melihat tingkat error rate hasil prediksi dengan nilai nyata dan R-Squared atau R2 untuk melihat korelasi kecelakaan dengan curah hujan. Hasil penelitian menunjukkan metode XGBoost mendapatkan nilai RMSE sebesar 0.120 pada data per hari dengan variabel kecelakaan saja sedangkan nilai R2 mendapatkan 0.19 pada data per 4 bulan kebelakang dengan variabel kecelakaan dan curah hujan.
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