A Model for Forecasting Production in Large-Scale and Smallholder Plantations in Indonesia - Tangkere, Ellen; Montolalu, Maya Hendrietta; Pakasi, Caroline Betsy Diana; Kaban, Maelani Ai (Jurnal Agroekoteknologi Terapan, 2025)
This study aims to develop a model that can predict the production of large plantation crops and smallholder plantations in Indonesia. The results are expected to contribute to the agricultural management strategy in Indonesia that allows this sector to continue to be one of the backbones of the national economy. The data collection method involves the annual report of the Indonesian Central Statistics Agency and global data published by the Food and Agricultural Organization from several decades ago to the present. Data analysis will involve time-series modeling, especially Auto Regressive Integrated Moving Average (ARIMA) and the latest machine-learning approach. The assessment of predictive ability is carried out through Receiver Operating Curves (ROC) curve analysis. The final model is selected based on the ability to predict the output of the simulation data. The ARIMA and NNAR models generally support the continued increase in palm oil seed production on large plantations in Indonesia at least until 2030. Meanwhile, coconut production, on the other hand, tends to continue to decline. These results indicate that the community that is the backbone of smallholder plantations needs to think in the long term to try to farm other production crops. This is because coconut plants, without changes in market demand, technological changes, or economic intervention, will continue to decrease in production in the coming years. Keywords: Production, Large Plantations, Smallholder Plantations