Identification of Suitable Crop Based on Weather Condition

Agriculture contributes significantly to the country's economic development. It is dependent on the weather and environmental factors such as climate, soil, fertilizers, flooding, precipitation, temperature crops, insecticides, pesticides and herbicides. Crop output is influenced by various factors making it difficult to forecast. In order to determine the current state of crop production various machine learning approaches are used to conduct a descriptive research on agriculture data. Farmers can use accurate crop production prediction model to assist them determine what to grow and when to grow. The K Nearest Neighbor, Random Forest, Support Vector Machine, Naive Bayes and Decision Tree algorithm are utilize to train the machine learning model. The best algorithm that suits our model should be identified and it is done by calculating the accuracy of each model.