Pembangkitan Data Sintetis pada Prediksi Transaksi Ekspor Kopi

Abstract

Coffee is a vital trade commodity for the global economy, including Indonesia, the third-largest coffee producer in the world in 2022/2023. This research aims to develop a predictive model for coffee export transactions using historical data and customer purchase trends. Due to the limited transaction data, synthetic data generation was employed to expand the dataset. The collected coffee export data was processed through several stages and then generated using the SDV Gaussian Copula. The results showed that the accuracy of the data generation was 74.87%, and the accuracy of the prediction was 61.5%.