Conceptual Modeling for Intelligent Knowledge-Based System in Agriculture: Case Study of Indonesia

Abstract

Agriculture is a pillar for economic growth in Indonesia. It drives the needs of agricultural information and knowledge increase. In order to provide information for farmers and knowledge to support the decision-making process in strategic level, the conceptual modeling for the intelligent knowledge-based system in agriculture is proposed. The conceptual model combines the geo-fencing technique to ensure the availability of information for farmers and machine learning to provide the knowledge for the strategic decision-making process in order to improve agricultural sector performance.