CROP RECOMMENDATION SYSTEM USING MACHINE LEARNING

Agriculture is essential for supporting human life, and choosing the right crops is important for achieving high productivity and securing a stable food supply. In traditional farming, decisions about which crops to grow are often based on the experience and judgment of farmers. However, this method may not always lead to the best crop choices when conditions such as soil quality and climate change. To overcome this issue, a Crop Recommendation System based on Machine Learning has been suggested. This system considers key factors like soil characteristics (including nitrogen, phosphorus, potassium, and pH levels), weather conditions (such as temperature, humidity, and rainfall), and other environmental elements to recommend the most appropriate crops for farming. Using classification algorithms, the system learns from data on agricultural practices and can accurately predict which crops are most suitable for a given area. This method helps farmers make informed decisions, increases crop yields, minimizes waste of resources, and promotes environmentally friendly farming. The system aims to connect traditional farming techniques with modern technology, offering farmers smart tools that improve the overall effectiveness of agricultural activities.