Implementasi Algoritma Backpropagation Dalam Memprediksi Harga Bahan Pangan

Deni Saputra (STIKOM Tunas Bangsa, Pematangsiantar, Medan, Indonesia)
M Safii (AMIK Tunas Bangsa, Pematangsiantar, Medan, Indonesia)
M Fauzan (STIKOM Tunas Bangsa, Pematangsiantar, Medan, Indonesia)

Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Vol 1, No 4 (2020): Edisi Oktober

Foodstuffs are raw materials in the form of agricultural, vegetable, and animal products used by the food processing industry to produce a food product. Prices of foodstuffs sometimes rise and fall erratically. The purpose of this research is to predict the price of foodstuffs by using the Backpropagation algorithm. The data used in this study is food price data from 2016 to 2019, originating from the Pusat Informasi Harga Pangan Statistics (PIHPS). This research uses the neural network method of the Backpropagation algorithm, which uses several architectural models, and the results of this test will yield the best accuracy value.