LCGC Car Demand Forecast Analysis with Two Forecasting Method (case studies of consumer in Indonesia) - Tri Wisudawati; Indah Wahyu Utami; Retna Dewi Lestari; Wahyu Adhi Saputro (Proceeding of International Conference on Science, Health, And Technology, 2021)
The economy of a country is basically supported by many sectors, one of which is the automotive industry sector with the designation as a provider of transportation facilities. The policy regarding transportation facilities is supported by the ministry of industry which issued a policy on environmentally friendly cars or low cost green cars (LCGC). Apart from being environmentally friendly, the car also has an affordable price in the community. Forecasting sales of LCGC cars is important for many companies that use past sales data to predict the amount of production that must be done so that goods continue to sell according to company targets. This will have an impact on the life and death of the automotive industry sector in the region. Important forecasting is done by many companies that use past sales data to predict the amount of production that must be done so that goods continue to sell according to the company's target. The data used in this research is secondary data. The secondary data needed in this study is the data on LCGC car sales in Indonesia from December 2019 to November 2020 obtained from secondary data sources. The data analysis method used in this research is exponential smoothing and trend analysis using POM QM software for Windows. The results also show that a good method to use as a sales forecasting method is the exponential smoothing method. This is because this method has a smaller MAPE value than the MAPE value in the trend analysis method. The MAPE figure for exponential smoothing is 4.9%, while the MAPE figure on the trend analysis method is 6.69%. In the exponential smoothing method, it is predicted that the sales of LCGC type cars in the next period are approximately 8448 units, while according to the trend analysis method, the sales forecast for the next period is 3894 units.