Non-Linear Trend Analysis to Forecast The Number of New Two-Wheeled and Four-Wheeled Vehicles in Manokwari Regency

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Patresia Sinaga
Universitas Papua
Esther Ria Matulessy
Universitas Papua
Nurhaida Nurhaida
Universitas Papua

Forecasting is a systematic effort that employs scientific methods (knowledge and technology) to predict future events. Trends depict patterns of time series data over long or significant time intervals, indicating a tendency to either rise or fall. Trend lines are not always linear; they can have a curved (non-linear) shape. Non-linear trends refer to trend models that involve quadratic, cubic, and so on equations. Based on the non-linear trend-shaped data plot and research objectives, non-linear trend analysis is used to forecast the number of motor vehicles in Manokwari Regency. The best model for forecasting the number of new two-wheeled vehicles is the cubic trend model, which is: with a MAPE of 7.8%, categorized as excellent. The best model for forecasting the number of new four-wheeled vehicles is also the cubic trend model, which is: with a MAPE of 5.7%, categorized as excellent.


Keywords: non-linear trend analysis, new two-wheeled and four-wheeled vehicles, forecasting