Jaringan Syaraf Tiruan Dalam Memprediksi Jumlah Produksi Daging Sapi Berdasarkan Provinsi

Abstract

Prediction is a process for estimating how many needs will be in the future. This study aims to predict the amount of beef production by province. Beef is one source of protein which is also a high value comodities. Meat production in Indonesia in general tends to increase by around 2.76% per year. But along with the increase in beef production in Indonesia, the level of meat consumption in Indonesia tends to fluctuate in recent years. Imports are the most common step taken by the government to meet domestic beef needs. By using the Artificial Neural Network and backpropagation algorithm, it will be predicted the amount of beef production based on the province in order to determine the steps to meet domestic beef demand based on the amount of beef consumption in the community. This study uses 11 input variables, namely data from 2005 to 2016 with 1 target, data of 2017. Using 5 architectural models to test the data to be used for prediction, the 11-4-1 model, 11-8-1 , 11-18-1, 11-20-1 and 11-28-1. Obtained the results of the best architectural model is the 11-28-1 architectural model with truth accuracy of 100%, the number of epochs 15 and MSE is 0.008623197. This model will be used in predicting the amount of beef production by province.Keywords : Beef production, prediction, backpropagatin, Artificial Neural Network

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“…Beef is one of the foodstuffs which has high protein and is the best medium for the growth of microorganisms [2]. This study is in accordance with the opinion of [3] which states that meat is a source of protein which is also a high-value commodity. The content contained in beef makes the meat rot quickly so we need processing technology to extend the shelf life such as fermentation techniques.…”

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Peramalan Jumlah Populasi Sapi Potong di Kalimantan Selatan Menggunakan Metode Moving Average, Exponential Smoothing dan Trend Analysis

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