
Autoregressive Integrated Moving Average (Arima) Dalam Memprediksi Jumlah Penjualan Frame
Author(s) -
Pristiwanto
Publication year - 2022
Publication title -
jatilima
Language(s) - English
Resource type - Journals
eISSN - 2722-0907
pISSN - 2721-1800
DOI - 10.54209/jatilima.v2i1.142
Subject(s) - autoregressive integrated moving average , box–jenkins , frame (networking) , operations research , photography , computer science , time series , marketing , business , economics , engineering , management , telecommunications , machine learning
Ektaco Sumber Foto is a company engaged in photo printing and is one of the largest photo labs in, which serves and facilitates photography needs for photographers. Ektaco Sumber Foto serves every day and facilitates the needs of photographers such as photo printing, frames, exclusive albums and press albums. The world of photographers is experiencing very rapid development from the film era to the digital era, which makes consumers changing modernize photographer prints with certain and sizes and combine them with photo frames. Forecasting is forecasting something that hasn't happened yet. This research was conducted with quantitative forecasting methods. The Box-Jenkins Periodic Series (ARIMA) method is a forecasting method that involves statistical analysis of past data. This ARIMA completely ignores the independent variables because this model uses the present values and past values of the independent variables to produce accurate short-term predictions or forecasts. Forecasting is important for every business organization and for every management decision making that is very significant. Forecasting is the basis for a company's long-term planning. The accuracy of the results of business forecasting will increase opportunities for achieving profitable investments in the company.