Weather conditions play a crucial role in various aspects of daily life, from influencing personal plans to affecting economic activities. In Seattle, known for its frequent rainfall and varying weather patterns, accurately predicting weather conditions can help residents and businesses make informed decisions. This project aims to develop a predictive model to forecast maximum daily temperatures based on historical weather data. By leveraging statistical and machine learning techniques, we aim to provide insights into the key factors driving temperature variations and enhance the ability to predict future weather conditions.

The data simulation in this data analysis tries to read the direction of the ideology of society in the Jakarta area, with a sample of one area consisting of 100, so that the data consists of 500 samples.

Overview of the Rock Garden at CUBG

PACC Flow