BibTex Citation Data :
@article{J.Gauss37797, author = {Vika Ersita and Yuciana Wilandari and Sugito Sugito}, title = {METODE TRIPLE EXPONENTIAL SMOOTHING HOLT-WINTER’S MULTIPLICATIVE DAN DEKOMPOSISI KLASIK MULTIPLIKATIF UNTUK PERAMALAN RATA-RATA KENAIKAN KONSENTRASI KARBON DIOKSIDA (CO2) GLOBAL}, journal = {Jurnal Gaussian}, volume = {12}, number = {3}, year = {2024}, keywords = {Increase in Carbon Dioxide Concentration; Triple Exponential Smoothing Holt-Winter's Multiplicative; Multiplicative Classical Decomposition; MAPE}, abstract = {Global warming occurs due the high concentration of Greenhouse Gases (GHG) in the atmosphere, which is called the greenhouse effect. The highest greenhouse gas that causes global warming that is being piled up in the atmosphere due human activity is carbon dioxide. Data on the average increase in global carbon dioxide (C02) concentrations are assumed contain elements of trend and seasonality. Holt-Winter's Multiplicative Triple Exponential Smoothing Method and Multiplicative Classical Decomposition the best choices in predicting data that contains trend and seasonality elements. Forecasting data on the global average increase CO2 has the objective of predicting data for the next 12 periods. The data used is data on the global average increase for the period January 2013 to December 2022. The prediction error measure used is MAPE (Mean Absolute Percentage Error). The results of the analysis on the Triple Exponential Smoothing Holt-Winter's Multiplicative method obtained a MAPE value of 0.09395%, indicating very good prediction category, while the results of the analysis of the Multiplicative Classical Decomposition method had a MAPE value of 0.07021%, which means that it has very good category in do forecasting. Based on the MAPE value obtained, the best method is the Multiplicative Classical Decomposition method.}, issn = {2339-2541}, pages = {434--444} doi = {10.14710/j.gauss.12.3.434-444}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/37797} }
Refworks Citation Data :
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
