Forecast Analysis of Fruit Supply Using Time-Series Method: A Study at PT Aerofood Indonesia

Abstract

PT Aerofood Indonesia is an entity operating in the aviation logistics industry, specifically as a partner of the Garuda Indonesia airline.  The main problem faced is the tendency to have excessive supplies of raw materials, especially in the aspect of purchasing fruit because it is susceptible to damage. This phenomenon often recurs and peaks beyond dry goods capacity limits, especially the availability of papaya fruit which often exceeds capacity by more than 50%. Therefore, this research aims to identify the optimal forecasting method for papaya fruit to overcome the problem of excessive stock. In this research, four forecasting approaches were tested, namely Trend Analysis, Single Average Exponential, Double Average Exponential, and Holt's Winter Method. Forecasting calculations were carried out using a manual approach and supported by Minitab 18 software. The research results showed that the Holt's Winter method with a multiplicative approach produced the lowest Mean Absolute Percentage Error (MAPE), namely 16%.  The Holt's Winter method with a multiplicative approach has proven to be effective in producing accurate forecasts. By implementing this recommended forecasting method, it is hoped that companies can be more efficient in managing inventory and reduce the impact of losses due to excess stock.