CD Skripsi
Penerapan Metode Autoregressive Integratedmoving Average (Arima) Untuk Memprediksipenjualan Suku Cadang Mobil Pada Subur Motor
Sales forecasting is a critical component of an effective business strategy, allowing companies to plan production, manage inventory, and make better marketing decisions going forward. Subur Motor is a company that provides products in the form of car parts and also serves car services. The increasing number of companies that are also engaged in the same field has forced Subur Motor to compete competitively with other companies. One of the efforts that Subur Motor can make in competing is to increase product sales. This study aims to predict the sales of car parts at Subur Motor using the Autoregressive Integrated Moving Average (ARIMA) method. The ARIMA method was chosen because it can handle non-stationary time series data and combines aspects of autoregressive (AR) and moving average (MA). The data used in this study are monthly sales data from May 2021 to September 2022. The ARIMA modeling process begins with the identification, estimation, and diagnosis of the appropriate ARIMA model. The results of this study show that the ARIMA (1,1,1) model provides good predictive value results compared to the other two models, namely ARIMA (0,1,1), and ARIMA (1,1,0). The ARIMA (1,1,1) model has been successfully tested significantly with a p-value of 0.000 smaller than the alpha value of 0.05, accompanied by an evaluation of the model accuracy measurement using the Mean Squared Error (MSE) of 34.099.
Keywords : ARIMA, Business Strategy, Forecasting, Time Series.
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