@inproceedings{85292c102d7441fbb2d8976d85afac78,
title = "Rainfall Prediction in Tengger Indonesia: A System Dynamics Approach",
abstract = "Commonly, rainfall prediction uses historical data or the time series data. But there are many factors can affect rainfall such as temperature and humidity. Therefore, an approach is needed that can model forecasting rainfall not only uses time series data but also includes other supporting variables. System dynamics is an approach for modeling and simulation of the data. By modeling the rainfall data from the previous year which includes temperature and humidity data using system dynamics, prediction of rainfall can be simulated. The prediction results using systems dynamics approach generate root mean square error (RMSE) smaller than previous studies. The result of RMSE with system dynamics for Puspo area is 6.767. It is smaller than the RMSE results with a hybrid Tsukamoto FIS with genetic algorithm method which is 7.30.",
keywords = "Indonesia, Prediction, Rainfall, System dynamics, Tengger",
author = "Ida Wahyuni and Adipraja, \{Philip Faster Eka\} and Mahmudy, \{Wayan Firdaus\} and Atiek Iriany",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Cyber Physical, Computer and Automation Systems, CPCAS 2019 ; Conference date: 13-11-2019 Through 15-11-2019",
year = "2021",
doi = "10.1007/978-981-33-4062-6\_17",
language = "English",
isbn = "9789813340619",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "197--210",
editor = "Endra Joelianto and Arjon Turnip and Augie Widyotriatmo",
booktitle = "Cyber Physical, Computer and Automation System - A Study of New Technologies",
}