Penerapan Metode Peramalan untuk Identifikasi Permintaan Konsumen

  • Karina Auliasari Institut Teknologi Nasional Malang
  • Mariza Kertaningtyas Jurusan Teknik Mesin DIII Institut Teknologi Nasional Malang
  • Mawan Kriswantono Jurusan Teknik Mesin S-1 Institut Teknologi Nasional Malang


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.

How to Cite
AULIASARI, Karina; KERTANINGTYAS, Mariza; KRISWANTONO, Mawan. Penerapan Metode Peramalan untuk Identifikasi Permintaan Konsumen. INFORMAL: Informatics Journal, [S.l.], v. 4, n. 3, p. 121-129, jan. 2020. ISSN 2503-250X. Available at: <>. Date accessed: 30 may 2024. doi: