Jurnal Gaussian
Vol 12, No 3 (2023): Jurnal Gaussian

METODE TRIPLE EXPONENTIAL SMOOTHING HOLT-WINTER’S MULTIPLICATIVE DAN DEKOMPOSISI KLASIK MULTIPLIKATIF UNTUK PERAMALAN RATA-RATA KENAIKAN KONSENTRASI KARBON DIOKSIDA (CO2) GLOBAL

Ersita, Vika (Unknown)
Wilandari, Yuciana (Unknown)
Sugito, Sugito (Unknown)



Article Info

Publish Date
26 Feb 2024

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.

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Journal Info

Abbrev

gaussian

Publisher

Subject

Other

Description

Jurnal Gaussian terbit 4 (empat) kali dalam setahun setiap kali periode wisuda. Jurnal ini memuat tulisan ilmiah tentang hasil-hasil penelitian, kajian ilmiah, analisis dan pemecahan permasalahan yang berkaitan dengan Statistika yang berasal dari skripsi mahasiswa S1 Departemen Statistika FSM ...