IMPLEMENTASI ALGORITMA BACKPROPAGATION UNTUK MEMPREDIKSI JUMLAH PENGUNJUNG WISATA MUSIUM (STUDI KASUS DI MUSIUM SUNAN DRAJAT)
DOI:
https://doi.org/10.30736/jti.v6i1.518Keywords:
peramalan, jaringan syaraf tiruan, backpropagationAbstract
Metode peramalan dalam teknologi komputasi sangatlah beragam, beberapa metode yang ada antara lain Peramalan ARIMA, Adaptive Neuro-Fuzzy Inference System (ANFIS), dan Jaringan Saraf Tiruan (JST). Pada artikel ini menyampaikan tentang usaha sebuah penelitian dengan tujuan untuk menerapkan dan mengetahui kinerja jaringan saraf dalam memprediksi jumlah pengunjung wisata museum (studi kasus di musium Sunan Drajat Lamongan). Metode yang digunakan adalah Matlab yang digunakan untuk menganalisis sebuah data yang kemudian dibentuk sebuah arsitektur jaringan terbaik aktif meramalkan jumlah pengunjung musium Sunan Drajat dengan skema 2-6-1 (2 neuron masukan, lapisan tersembunyi 6 neuron, satu neuron output) dengan nilai MSE terkecil 0,00000000277. Nilai MSE selama pelatihan sebesar 7858.75 sedangkan pada saat pengujian di 5.309.807.667. Kesalahan rata-rata hasil simulasi peramalan jumlah wisatawan ke musium Sunan Drajat dalam periode dari Maret hingga Mei 2019 sebesar 9,5%.Downloads
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