Track: Entrepreneurship and Innovation

Abstract

Agricultural price prediction is an effort to anticipate the impact of changes in product prices. Various methods have been used to predict the prices of various agricultural products. The purpose of this study is to review various methods of predicting agricultural product prices in the literature study and to provide future research challenges. A comprehensive review of the research topic is presented in the Systematic Literature Review. The text mining approach is used to see an overview of research based on the appearance of words in the article. The results showed that the methods commonly used to predict the price of agricultural products are Neural Networks (30%), Data Mining (22%) and Regression (18%). The contribution of this research includes the latest research positions, recommendations for the best methods and proposals for future research taking into account the current pandemic conditions.