BibTex Citation Data :
@article{J.Gauss39141, author = {Haniatul Mutamakkinah and Rukun Santoso and Tarno Tarno}, title = {PERBANDINGAN METODE ARIMA DAN MODEL FUNGSI TRANSFER UNTUK MERAMALKAN CURAH HUJAN DI JAWA TENGAH PERIODE TAHUN 2023-2024}, journal = {Jurnal Gaussian}, volume = {13}, number = {2}, year = {2024}, keywords = {ARIMA; MAPE; Rainfall; Transfer Function}, abstract = { Analysis data of time series is basically used for analysis data that makes the effect of observations on the previous period. The role of forecasting has explored various fields, including the field of meteorology which concerns weather forecasting. The ARIMA model is a forecasting model for analyzing single time series data and only look into the dependence of rainfall on past data without involving other variables. The transfer function has an output tier (y t ) which is expected to be affected by the input tier (x t ) or other inputs which called the noise tier (n t ). The purpose of this research is to find out which method is most appropriate to use in forecasting rainfall in the region of Central Java. Forecasting results with the transfer function model will be compared with the rainfall ARIMA model in Central Java to find out which method is more preferable. The data used in the research are rainfall data and air temperature, in Central Java from January 2016 to December 2022. The results showed that the MAPE value with transfer function model is 38,21%, while the ARIMA model has an MAPE value of 43,23%. From the MAPE value we can conclude that transfer function method is the best forecasting model for rainfall forecasting rather than ARIMA, because the MAPE value is tinier. }, issn = {2339-2541}, pages = {280--288} doi = {10.14710/j.gauss.13.2.280-288}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/39141} }
Refworks Citation Data :
Analysis data of time series is basically used for analysis data that makes the effect of observations on the previous period. The role of forecasting has explored various fields, including the field of meteorology which concerns weather forecasting. The ARIMA model is a forecasting model for analyzing single time series data and only look into the dependence of rainfall on past data without involving other variables. The transfer function has an output tier (yt) which is expected to be affected by the input tier (xt) or other inputs which called the noise tier (nt). The purpose of this research is to find out which method is most appropriate to use in forecasting rainfall in the region of Central Java. Forecasting results with the transfer function model will be compared with the rainfall ARIMA model in Central Java to find out which method is more preferable. The data used in the research are rainfall data and air temperature, in Central Java from January 2016 to December 2022. The results showed that the MAPE value with transfer function model is 38,21%, while the ARIMA model has an MAPE value of 43,23%. From the MAPE value we can conclude that transfer function method is the best forecasting model for rainfall forecasting rather than ARIMA, because the MAPE value is tinier.
Note: This article has supplementary file(s).
Article Metrics:
Last update:
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Media Statistika journal and Department of Statistics, Universitas Diponegoro as the publisher of the journal. Copyright encompasses the rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.
Jurnal Gaussian and Department of Statistics, Universitas Diponegoro and the Editors make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in Jurnal Gaussian journal are the sole and exclusive responsibility of their respective authors and advertisers.
The Copyright Transfer Form can be downloaded here: [Copyright Transfer Form Jurnal Gaussian]. The copyright form should be signed originally and send to the Editorial Office in the form of original mail, scanned document or fax :
Dr. Rukun Santoso (Editor-in-Chief) Editorial Office of Jurnal GaussianDepartment of Statistics, Universitas DiponegoroJl. Prof. Soedarto, Kampus Undip Tembalang, Semarang, Central Java, Indonesia 50275Telp./Fax: +62-24-7474754Email: jurnalgaussian@gmail.com
Jurnal Gaussian by Departemen Statistika Undip is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Visitor Number:
View statistics
