Komparasi Metode Grey GM (1.1) Dan Grey Verhulst Untuk Prediksi Harga Sembako

The problem of availability and affordability of basic necessities is the main problem that receives complaints from the public, with a focus on price fluctuations which are influenced by factors such as seasonal variations and weather conditions.The pressing problem of increasing demand for food amidst Indonesia's population growth is exacerbated by price fluctuations.This research uses gray forecasting methods, namely GM (1.1) and gray Verhulst to predict prices of basic commodities in East Java.This research aims to determine the level of accuracy of the Gray Model and Gray Verhulst methods for predicting basic food prices.The comparison results show that gray Verhulst is superior in predicting the price of certain commodities, such as Premium Rice, while GM (1.1) is proven to be more effective for the sugar category.This finding was obtained from analysis of the ARPE value which shows the accuracy of the model in price prediction.The lowest error rate for gray Verhulst was 1.9471% for premium rice, and the highest was 64.535% for sugar.For GM (1.1), the lowest error rate was 2.184% for medium rice and the highest was 6.633% for premium rice.