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Muhammad Marizal
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Jl. H.R. Soebrantas Km. 15.5 No. 155 Gedung Fakultas Sains dan Teknologi UIN Sultan Syarif Kasim Riau Kel. Tuahmadani Kec. Tampan Pekanbaru - Riau 28293
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Indonesian Council of Premier Statistical Science
Published by Universitas Islam Negeri Sultan Syarif Kasim Riau
ISSN : -     EISSN : 30309956     DOI : http://dx.doi.org/10.24014/icopss.v2i1.25322
Core Subject : Economy, Health, Science, Education, Social,
Computer Science & IT Economics, Econometrics & Finance Mathematics Public Health Social Sciences
Indonesian Council of Premier Statistical Science (ICoPSS) established in 2022, publishes scientific papers in the area of statistical science and its applications with E-ISSN 3030-9956. The published papers should be research papers with, but not limited to, the following topics: experimental design and analysis, survey methods and analysis, operation research, data mining, statistical modeling, computational statistics, time series and econometrics, and statistics education. All papers were reviewed by peer reviewers consisting of experts and academicians across universities and agencies. Indonesian Council of Premier Statistical Science (ICoPSS) is a double-blind peer-reviewed international journal published by the Faculty of Science and Technology Universitas Islam Negeri Sultan Syarif Kasim Riau. Scope: Indonesian Council of Premier Statistical Science is a refereed journal committed to Statistics and its applications.
Arjuna Subject : Ilmu Pengambilan Keputusan (semua kategori) - Statistik, Kemungkinan dan Ketidak Pastian
Articles 41 Documents
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Forecasting of Average Air Temperature in the City of Pekanbaru Using the Holt-Winters Method Yendra, Rado; Marizal, Muhammad; Ramadhani, Hilvania
Indonesian Council of Premier Statistical Science Vol 4, No 2 (2025): August 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/icopss.v4i2.37868

Abstract

Global climate change causes significant fluctuations in air temperature, including in the city of Pekanbaru, therefore, a predictive system is needed that can help the government and the community in dealing with climate impacts, one of which is through air temperature forecasting. This study aims to forecast the average air temperature in Pekanbaru City using the Holt-Winters Exponential Smoothing method, which is known to be effective in capturing seasonal patterns and trends. The data used is monthly average air temperature data from 2017 to 2024 obtained from BMKG. The analysis was carried out using an addictive approach and model evaluation was carried out based on the Mean Absolute Percentage Error (MAPE) value. The results show that the best model is obtained on a parameter with a MAPE value of 2.684. This model is then used to forecast the air temperature in 2025, which is predicted to decrease gradually. The results of this forecast are expected to be a reference in planning and decision-making related to climate change mitigation in the Pekanbaru area

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