Prediksi Harga Pasar Daging Sapi Di Kota Malang Dengan Menggunakan Metode Extreme Learning Machine (ELM) - Cusen Mosabeth; Muhammad Tanzil Furqon; Randy Cahya Wihandika (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Beef is one of the basic needs whose existence is greatly increased in Indonesia. The need to consume beef is very sharp in proportion to the increase in population and the awareness of the importance of consuming very high nutritious foods. Basically the need for animal protein cannot be replaced with other proteins. Estimating future consumer demand by making production plans a challenge for an industry. This makes predictions play an important role. Effective and efficient design must be supported by an accurate prediction system. ELM Is an artificial neural network consisting of feed-forward with one or hidden layer-forwad neural. Therefore, in this study the author uses the Extreme Learning Machine (ELM) method. The experimental results showed that the ELM method had a good error measured by the Mean Absolute Percentage Error (MAPE) error rate of 0.344% using the ratio of the training data 90%: 10%, the input weight range between -1 and 1, the number of neurons in the hidden layer 7, then use the binary sigmoid activation function, and use the number of features 3. The results are proved by using the method of Extreme Learning Machine can predict the price of beef with accurate and precise and get the price of beef in the future.