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PREDIKSI TINGKAT KEPADATAN PENUMPANG TRANSJAKARTA SEBAGAI INDIKATOR KEMACETAN LALU LINTAS JAKARTA MENGGUNAKAN ALGORITMA RANDOM FOREST, DECISION TREE, DAN KNEAREST NEIGHBOR
data mining and knowledge discovery, machine learning, random forest, decision tree, k-nearest neighbor, transjakarta, capita selecta metode penelitian
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