Prediksi Penjualan Seblak menggunakan Algoritme Extreme Learning Machine di Seblak Malabar - Fadhlillah Ikhsan; Budi Darma Setiawan; Tibyani Tibyani (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Seblak Malabar is a business in Malang running on food sector. The typical uniqueness of flavor and the diversity of menu which make the food attract many customers. However, because of the impact of some factors, such as weather change and tighter market trend, makes Seblak sale run into the fluctuation. It makes some new problems; those are problem in maximizing the profit and maintaining the stability of logistics. From those problems, the upcoming selling prediction is a solution offered by the researcher because it has an important role to make a decision. The data used for this prediction refers to the previous sale data. That data is time series because it is arranged based on the time. Time series data prediction is very complex problem so that it is needed a method which is able to produce a prediction based on previous data pattern movement. Extreme Learning Machine Algorithm in Artificial Neural Network (ANN) feedforward network is suggested by the researcher because it has very good performance in predicting time series data. From the research conducted, ELM algorithm is able to produce Mean Average Percentage Error (MAPE) up to 1.7548%. MAPE score less than 10% indicates that ELM algorithm can be used to predict the sale of Seblak Malabar.