Wahyunika, Nuzuliana (2023) Analisa Dan Prediksi Cuaca Dan Curah Hujan Menggunakan Long Short Term Memory (lstm) Dan Bahasa Pemrograman Python (studi Kasus : Universitas Islam Riau,pekanbaru). Other thesis, Universitas Islam Riau.

Text 183510049.pdf - Submitted Version Download (6MB)

Abstract

Weather is a change in temperature, wind, precipitation, and sunlight. Weather forecasting is much needed because of the collaboration between science and technology to determine the Earth's atmosphere. Problems often encountered in predicting rainfall include unstable atmospheric conditions, measurement errors, data that is too large, and an incomplete understanding of the performance of rainfall forecasts resulting in inaccurate predictions that allow prediction of erratic rainfall. Thus, researchers want to make an analysis of weather and rainfall forecasts with a history of previously collected data. the Long Short Term Memory (LSTM) algorithm is used to predict the amount of precipitation, while the python language plots the occurrence of precipitation. The processed Data came from the computer database of the Robotics Laboratory, the data was collected using a tool in the form of davis weather station installed on the rooftop of building a faculty of engineering UIR. This tool serves to collect raw data in the form of weather parameters. The data that has been collected is stored in the database with the help of the davis weatherlink application from March to December 2022, with a total of 278 data records grouped per week. Then the prediction accuracy of MAPE is 86.33% with a value of 13.466.

Actions (login required)

View Item