FORECASTING RED CHILLI PRICE USING HOLT-WINTERS EXPONENTIAL SMOOTHING
Egi Abinowi, Muhammad Rozahi Istambul and Hari Supriadi
Engineering Faculty of Widyatama University
Abstract
Strategic agricultural commodities such as chili have an important role in the Indonesian economy because it is the main consumption of the community which is used as a cooking spice. The need for large consumption of chili commodities is very influential. Unstable chili commodity market prices can harm farmers, traders and consumers. Then a method is needed to predict the price of red chili. Forecasting is the art and science of predicting events that will occur by using historical data and projecting it into the future with several forms of mathematical modeling. Forecasting, certain methods are needed and which method is used depends on the type of data to be predicted and the objectives to be achieved. This study uses the Holt-Winters Exponential Smoothing forecasting method. The Holt-Winters Exponential Smoothing method is a forecasting method with an exponential smoothing approach based on forecasting results in the previous period. This method also adds parameters to handle seasonal data patterns. This study uses Bandung City red pepper price data from 2016 to 2018. From the results of this study using the HOLT-WINTER MARKETING EXPONENTION method the additive model with a value of α,β, ? 0.1 resulted mean absolute percentage error (MAPE) error of 15.4% obtained from comparison of actual data and forecast on year 2018.
Keywords: Forecasting; Data Mining; Holt-Winters Exponential Smoothing
Topic: Informatic and Information System