Prediksi Jumlah Kendaraan di Provinsi Riau Menggunakan Metode Backpropagation

Authors

DOI:

https://doi.org/10.30872/jim.v14i1.1745

Keywords:

Prediksi, Backpropagation, Kendaraan, Riau

Abstract

Riau adalah salah satu provinsi yang berada di Indonesia. Banyak akvititas masyarakat baik di bidang pemerintahan, pendidikan, perdagangan, industri, dan transportasi. Provinsi Riau mengalami pertumbuhan penduduk yang cukup tinggi dari tahun ke tahun, karena banyaknya jumlah orang yang berimigrasi dari daerah atau pronvinsi lain. Pertumbuhan populasi penduduk juga meningkatkan jumlah kendaraan yang ada di Riau. Metode penelitian ini terdiri dari beberapa tahap termasuk pengumpulan data, pemilihan data, proses menggunakan metode backpropagation dan analisis dan evaluasi. Berdasarkan hasil pelatihan dan pengujian yang telah dilakukan, algoritma Backpropagation dapat memprediksi jumlah kendaraan di Riau. Dalam pelatihan, fase prediksi hasil dipengaruhi oleh nilai tingkat belajar, jumlah neuron yang tersembunyi, dan jumlah epoch, semakin kecil pentingnya pembelajaran maka semakin lama proses pembelajaran, serta nama zaman. Hasil prediksi yang dilakukan ada peningkatan jumlah sepeda motor, mobil penumpang, truk dan bus mobil sekitar 1% dengan nilai kesalahan MSE 0,0016168.

References

Badieah, Gernowo, R., & Surarso, B. (2016). Metode Jaringan Syaraf Tiruan Untuk Prediksi Performa Mahasiswa Pada Pembelajaran Berbasis Problem Based Learning (PBL). Jurnal Sistem Informasi Bisnis, 6(1), 46–58. https://doi.org/10.21456/vol6iss1pp46-58

Fausett, L. V. (1994). Fundamentals of Neural Networks Architectures, Algorithms, and Application. Prentice Hall.

Gupta, B. B., Joshi, R. C., & Misra, M. (2012). ANN Based Scheme to Predict Number of Zombies in a DDoS Attack. International Journal of Network Security, 14(2), 61–70. Retrieved from http://ijns.jalaxy.com.tw/contents/ijns-v14-n2/ijns-2012-v14-n2-p61-70.pdf

Hermawan. (2006). Jaringan Syaraf Tiruan Teori dan Aplikasi. Andi Yogyakarta.

Kusumodestoni, R. H. (2015). PREDIKSI FOREX MENGGUNAKAN MODEL NEURAL NETWORK. Jurnal SIMETRIS, 6(2), 205–210.

Lubis, L. S., & Buono, A. (2012). Pemodelan Jaringan Syaraf Tiruan Untuk Memprediksi Awal Musim Hujan Berdasarkan Suhu Permukaan Laut. Jurnal Ilmu Komputer Agri-Informatika, 1(2), 52–61.

Murtopo, A. A. (2015). Prediksi Kelulusan Tepat Waktu Mahasiswa STMIK YMI Tegal Menggunakan Algoritma Naïve Bayes. CSRID Journal, 7(3), 145–154.

Pustaningrum, D. (2009). Pengantar Jaringan Saraf Tiruan. Andi.

Siang, J. J. (2009). Jaringan Syaraf Tiruan. Yogyakarta: Andi.

Sinaga, F. M. F. (2017). Backpropagation Untuk Prediksi Kelulusan Siswa Sekolah Mengenah Atas (Studi Kasus : SMA CAHAYA MEDAN ). Majalah Ilmiah Inti, 12(1), 88–95.

Smith, A., & Sya’diyah, Z. (2017). Peramalan Jumlah Kendaraan di DKI Jakarta dengan Jaringan Backpropagation. Barekeng Jurnal Ilmu Matematika Dan Terapan, 10(2), 117–125.

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Published

2019-02-28

Issue

Vol. 14 No. 1 (2019): Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer

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