Open AccessPenerapan Metode Peramalan untuk Identifikasi Permintaan Konsumen
Author(s) -
Karina Auliasari,
Mariza Kertaningtyas,
Mawan Kriswantono
Publication year - 2020
Publication title -
informal
Language(s) - English
Resource type - Journals
ISSN - 2503-250X
DOI - 10.19184/isj.v4i3.14615
Subject(s) - forecast error , scheduling (production processes) , term (time) , computer science , operations research , statistics , demand forecasting , econometrics , operations management , mathematics , economics , physics , quantum mechanics
The forecast model is done using data from several years before, with the involvement of time parameters in the forecast process is usable for the company to made an effective and efficient planning. Forecasting has an important role because the company requires short-term, medium-term and long-term estimates for each management. For short-term estimates, a company requires personnel, production and transportation scheduling, which is part of the process of scheduling and estimating consumer demand. In this study the results of three forecasting methods were compared, there is simple average, naïve and seasonal naive on demand data of PT SUPER SUKSES NIAGA to be further these three method measured its forecast accuracy using the value of MASE (Mean Absolute Square Error). From the results of data pre-processing consumers whose high value of demand are PT. DIESELINDO, PT. DUTA, PT. HEXINDO and PT. PANATAMA. The results of forecasting shown that the method that has the smallest MASE value is the simple moving average method.