Prediksi Inflasi menggunakan Indeks Harga Konsumen Kota Malang dengan Metode Extreme Learning Machine - Muhamad Altof; Nurul Hidayat; Marji Marji (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2021)
Countries that experience a decrease in the value of their currency are often said to be inflation, where when inflation occurs the prices of goods and services will increase, if this situation is not anticipated by policy makers and the public it will have a negative impact on daily life, with these problems the prediction system will be very help to measure the rate of inflation, an indicator called the Consumer Price Index is needed, this will calculate the mean value of the price of goods used by the public, within a certain time, to overcome this problem, a system that can predict the rate of inflation quickly and accurately is needed. The ELM method is included in the Artificial Neural Network, ELM is divided into a training and testing process, then an evaluation of the error rate is carried out using the Mean Absolute Percentage Error method, after being tested 10 times using the parameter number of features as many as 4, 6 neurons, comparison With 60% training data, 40% testing, the lowest error rate is 1.54%, which means that the ELM method has high speed and accuracy.