Rainfall is a very important factor in daily life, especially in agriculture and water resources management. Accurate rainfall forecasts are essential to mitigate the impact of floods, droughts, and water shortages. This study aimed to predict rainfall in Tegal City using data on rainfall, temperature, humidity, and barometric pressure. Explore association rules to define relationships between elements to predict weather. Then, the data is processed using a priori algorithms to find patterns of relationships between variables in the data. The results showed that a priori algorithms can be used to find ways of association that can be used to predict rainfall in Tegal City. Based on the research results and discussions that have been carried out, it can be concluded that the Association Rule method using a priori algorithm can be applied quite well in rainfall forecasting simulations in Tegal City. Based on the analysis, it was found that some association rules have a lift ratio value greater than 1, thus indicating that these rules have a significant level of strength and can be relied upon as a guideline in forecasting rainfall in Tegal City. This method can help predict weather conditions and provide useful information for the public and authorities to decide on outdoor activities.
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