The Effect of Weather On Agricultural Results Using Naïve Bayes Calculation

Abstract

This study aims to predict crop yields based on weather data using the Naive Bayes algorithm. Extreme weather factors such as high temperatures, low humidity, and unpredictable rainfall often affect crop yields in Indonesia. In this research, weather data, including temperature, humidity, and rainfall, were used to predict the yields of three types of crops: corn, chili, and tomatoes. The Naive Bayes algorithm was applied for classification, with the output being classified as low, medium, or high yield. The results showed that high temperatures and low rainfall significantly negatively impacted the yield of corn, while chili and tomato plants were more resistant to such extreme weather conditions. This research provides insights into the use of technology to enhance agricultural yields by planning planting and harvesting times based on weather predictions.