PERAMALAN HARGA BERAS MENGGUNAKAN METODE HYBRID AUTOREGRESSIVE INTEGRATED MOVING AVERAGE DAN NEURAL NETWORK (ARIMA-NN)

Manuela Visakha, Dhoriva Urwatul Wutsqa

Abstract


Penelitian ini bertujuan untuk mendeskripsikan model dan ketepatan hasil Hybrid ARIMA-NN dalam meramalkan harga beras di Indonesia tahun 2015-2021 yang bersumber dari Badan Pusat Statistik. Hybrid ARIMA-NN adalah model gabungan model Autoregressive Intregated Moving Average (ARIMA) dan Neural Network. Peramalan dilakukan dengan cara melakukan pemodelan ARIMA terlebih dahulu, kemudian residual dari ARIMA dimodelkan dengan Neural Network. Algoritma dalam Neural Network yang digunakan dalam penelitian ini adalah backpropagation. Hasil peramalan menggunakan Hybrid ARIMA-NN diukur keakuratannya menggunakan Mean Absolute Percentage Error (MAPE). Hasil penelitian ini diperoleh model Hybrid ARIMA(2,0,0) dan NN(2,9,1) yang terdiri dari AR dengan ordo 2, differencing dengan ordo 0, dan MA dengan ordo 0 kemudian model Neural Network dengan 2 neuron input, 9 neuron tersembunyi, dan 1 neuron output. Hasil akurasi model Hybrid ARIMA-NN diperoleh nilai MAPE sebesar 0,9778% yang menunjukkan bahwa model memiliki tingkat keakuratan yang baik.

Kata kunci: peramalan, harga beras, Hybrid ARIMA-NN, Autoregressive Intregated Moving Average, Neural Network.


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