Explainable AI Prediction of Cooking Oil Prices Over Time
Fachrizal Azzuri, Lazuardy Syahrul Darfiansa, Rahma Syndu Grananta, Ayu Indah Permatasari, Novanto Yudistira · 2022
Cooking Oil is an essential Commodity in household needs, so an uncertain price increase will significantly impact the Community’s Scope. This study aimed to determine the factors of high and low prices of Cooking Oil Based on Other Commodities. Therefore, this research was conducted based on predicting an increase in cooking oil prices from time to time determined by other commodities. We use Long Short-Term Memory (LSTM), one of the Machine Learning methods that can predict based on time series data efficiently (remembering a collection of information that has been stored for a long time and deleting information that is no longer relevant). Then it is implemented into the Explainable Artificial Intelligence (XAI) model, namely SHapley Additive ExPlanations (SHAP) using Random Forest, which is used in the explanation problem of machine learning models that can handle data sets containing Continue Variables as in the case of regression and categorical variables as in the case of classification. On Commodities that affect the Increase in Cooking Oil Prices.