Penerapan Metode Jaringan Saraf Tiruan Dalam Memprediksi Produksi Daging Domba Menurut Provinsi
- Listy Oktaviani STIKOM Tunas Bangsa, Pematang Siantar, Indonesia
- Sandy Erlangga STIKOM Tunas Bangsa, Pematang Siantar, Indonesia
- Bintang Aufa Sultan STIKOM Tunas Bangsa, Pematang Siantar, Indonesia
-
Agus Perdana Windarto
*
STIKOM Tunas Bangsa, Pematang Siantar,
Indonesia
- Putrama Alkhairi STIKOM Tunas Bangsa, Pematang Siantar, Indonesia
Abstract
Prediction is the process of estimating future needs. This research aims to predict the amount of sheep meat production by province. Lamb is a source of protein which is also a high value commodity. However, along with the increase in lamb production in Indonesia, the level of lamb meat consumption in Indonesia has tended to fluctuate in recent years. Imports are the step most often taken by the government to meet domestic sheep meat needs. By using Artificial Neural Networks and the backpropagation algorithm, the amount of sheep meat production will be predicted based on provinces in order to determine steps to fulfill domestic sheep meat needs based on the amount of sheep meat consumption in the community. This research uses data from 2001 to 2022 with 1 target, namely data for 2023.
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