Yamaha Nmax Motorcycle Demand Forecasting Model at Yamaha Rolya Motor Dealers with Exponential Smoothing Method
DOI:
https://doi.org/10.46799/ajesh.v1i3.18Keywords:
Demand Forecasting, Exponential Smoothing, MSEAbstract
Demand forecasting is basically a projection of the demand for a company's products or services. Forecasting is also referred to as forecasting sales. Rolya Motor's main problem lies in the fluctuating demand for Yamaha Nmax motorbikes, making demand targets not in accordance with what has been determined and excess or shortage of goods. Exponential smoothing is a moving average time series method that weighs past data exponentially so that the most recent data has greater weight. The purpose of this study is to forecast the demand for Yamaha NMAX motorcycles one season ahead and adjust them to future targets and inventory stocks using the Exponential Smoothing method. Trial and error method on parameter values 0,1<?< 0,9 ; 0,1<?<0,9 ; 0,1<?<0,9, indicating the smallest MSE value is located at point ? = 0,9; ? =0,1 ; ? =0,9 with a value of 0.058. Based on the research results, companies should use the Holt-Winter Exponential Smoothing method because it has quite good demand forecasting results when compared to the actual demand six months ahead in 2022.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Artowikocy Muhammad Keiran Prasetyo, Rr Erlina

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International. that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.