Algoritma Peramalan Time Series Levenberg-Marquardt, Fuzzy, Backpropagation dan ARIMA (Autoregressive Integrated Moving Average) - Much. Arafat Al Mubarok; Anik Nur Handayani (Universitas Ngeri Malang, 2022)
There are many methods used in forecasting, including forecasting using time series data. Forecasting using time series data is a favorite for forecasting both linear and non-linear data. Many researchers have contributed to the development of time series data analysis [1] such as C. Wang [2], Pouzols et al [3]. The results of this research literature study show that the Levenberg-Marquardt and Fuzzy algorithms are superior algorithms to the backpropagation and ARIMA algorithms. It is hoped that the results of this study can provide benefits to other researchers and can be used as a reference source. Terdapat banyak metode yang di gunakan dalam melakukan peramalan termasuk untuk melakukan peramalan menggunakan data time series. Peramalan menggunakan data time series menjadi favorit untuk melakukan peramalan baik data linier atau non linier. Banyak peneliti yang telah berkontribusi dalam pengembangan analisis data time series [1] seperti C. Wang [2], Pouzols et al [3]. Hasil studi literatur penelitian ini menunjukkan bahwa algoritma levenberg-marquardt dan fuzzy adalah algoritma yang lebih unggul daripada algoritma backpropagation dan ARIMA. Diharapkan hasil penelitian ini dapat memberikan manfaat bagi peneliti lain serta dapat di jadikan sumber rujukan.