CROP RECOMMENDATION AND PEST CONTROL TECHNIQUE IN AGRICULTURE USING MACHINE LEARNING

In the field of agriculture, the most common cause of crop failure is the incorrect choice of which kind of plant should be cultivated on a certain plot of land. In most cases, the farmers are unaware of the requirements that the crop has, such as the minerals, soil moisture, and other soil requirements. The farmer's mental health as well as their financial situation may suffer as a result of this. Farmers often face a number of challenges, one of which is the fact that they are not always aware of the pests and illnesses that might potentially impact the crops they raise in the early stages of the problem. This issue that faces farmers is discussed in our study, and with the assistance of a Recommendation System, we attempted to provide a solution to this problem. With the assistance of our model, we are able to provide forecasts regarding which crop will be most suited for the farmer, as well as identify any potential threats to the crop and make recommendations regarding how these threats might be mitigated. In this study, we used the SVM classification algorithm, the Decision Tree algorithm, and the Logistic Regression algorithm. After doing so, we came to the conclusion that the SVM classification model provides the highest level of accuracy compared to the other algorithms