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Ria Matulessy, Esther
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Social Sciences

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Non-Linear Trend Analysis to Forecast The Number of New Two-Wheeled and Four-Wheeled Vehicles in Manokwari Regency Sinaga, Patresia; Ria Matulessy, Esther; Nurhaida, Nurhaida
Journal of Social Research Vol. 3 No. 1 (2023): Journal of Social Research
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/josr.v3i1.1861

Abstract

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.
Application of The Double Exponential Smoothing Brown Method to Consumer Price Index Forecasting in Sorong City before and during The Covid-19 Pandemic Hidayah, Nurin; Ria Matulessy, Esther; Hilum, Rium
Journal of Social Research Vol. 3 No. 3 (2024): Journal of Social Research
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/josr.v3i3.1954

Abstract

The CPI is useful for knowing the increase in income, prices, can also be used as an economic indicator and a benchmark for the amount of production costs. The Consumer Price Index is often used to measure the level of increase or decrease (inflation/deflation) in the prices of goods and services that are the basic needs of the people of an area, as well as a consideration for salary adjustments, retirement wages and others. CPI forecasting in Sorong City is a solution to predict future economic conditions as seen from the increase or decrease in the CPI and choose the right countermeasure or strategy in dealing with the consequences of an increase (inflation) or decrease (deflation) in the CPI that will occur in the future. The Covid-19 Pandemic situation has greatly affected economic and social life, including the CPI in Sorong City. The purpose of this research is to obtain the right model in forecasting the CPI in Sorong City using the Double Exponential Smoothing Brown method, a forecasting method that uses one weighting parameter. The best model of forecasting before the Covid-19 pandemic using optimal weighting parameters with a MAPE value of 0.647%, namely: and the best model during the Covid-19 pandemic using optimal weighting parameters with a MAPE value of 0.633%. The forecasting model obtained, namely:
Co-Authors Hidayah, Nurin Hilum, Rium Nurhaida Nurhaida Sinaga, Patresia