Integration of Palm Oil Supply Chain Information System in Langkat Regency with Prospective Artificial Intelligence for Price Predictioand Distribution Optimization

Abstract

The palm oil supply chain in Indonesia faces persistent challenges, including price fluctuations, long distribution channels, and the weak bargaining position of smallholder farmers. This study analyzes the palm oil smallholder supply chain in Langkat Regency using the Food Supply Chain Network (FSCN) framework and designs a marketing information system prototype to improve transparency and efficiency. The proposed system allows farmers, traders, and palm oil mills (PKS) to access real-time price information and conduct transactions digitally, thereby reducing dependency on intermediaries and improving farmers’ income share. Although the current study focuses on the development of an information system, it also highlights the potential integration of Artificial Intelligence (AI) technologies. AI can be applied in price prediction, demand forecasting, and logistics optimization, which will strengthen decision-making and enhance supply chain performance. The findings suggest that while the prototype provides an initial solution for improving transparency, the integration of AI in future development presents significant opportunities to address systemic inefficiencies. This study contributes to the discussion on the role of digital transformation and AI in agricultural supply chains, particularly in improving smallholder welfare and market competitiveness.