PREDICTION OF AVERAGE TEMPERATURE IN BANYUWANGI REGENCY USING SARIMA

Climate change due to human activity has significantly impacted increasing global average temperatures, including in Banyuwangi Regency, East Java. The impact is felt in several sectors, such as agriculture, tourism, and health. As a preventive measure to minimize the adverse effects that will occur in the future, an accurate prediction of the average temperature of Banyuwangi Regency is needed. This research used secondary data from the official website of the Central Statistics Agency (BPS) of Banyuwangi Regency per month from January 2012 to December 2023. Predictions are made using the seasonal autoregressive integrated moving average (SARIMA) approach. The best model is selected based on its fulfillment of stationarity, the significance of its parameters, and compliance with the assumptions of normality and white noise. From this method, the best model obtained to predict the average temperature of Banyuwangi Regency is the probabilistic SARIMA (1,0,0)(0,1,1)12. The probabilistic SARIMA model treats both parameters and forecasts as probability distributions. The average temperature of Banyuwangi Regency is obtained for the next year, namely from January 2023 to December 2023, with a MAPE of 1.63%. With an accuracy rate of 98.37%, it can be said that the probabilistic SARIMA (1,0,0)(0,1,1)12 model is accurate in predicting the average temperature of Banyuwangi Regency in the future. Thus, the prediction of the average temperature of Banyuwangi Regency is expected to help the community and government manage the impact of erratic climate change to improve the welfare of all Banyuwangi people.

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Journal
BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN
Published
2025-07-01
DOI
https://doi.org/10.30598/barekengvol19iss3pp2207-2218
Primary Topic
Data Mining and Machine Learning Applications
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article
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article

PREDICTION OF AVERAGE TEMPERATURE IN BANYUWANGI REGENCY USING SARIMA

Sediono Sediono, Idrus Syahzaqi, Mega Kurnia Dyaksa, Anggi Triya Vionita et al.
BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN
Data Mining and Machine Learning Applications
article

PREDICTION OF AVERAGE TEMPERATURE IN BANYUWANGI REGENCY USING SARIMA

Sediono Sediono, Idrus Syahzaqi, Mega Kurnia Dyaksa, Anggi Triya Vionita, Anisah Nabilah Ghasani
article en

Abstract

Climate change due to human activity has significantly impacted increasing global average temperatures, including in Banyuwangi Regency, East Java. The impact is felt in several sectors, such as agriculture, tourism, and health. As a preventive measure to minimize the adverse effects that will occur in the future, an accurate prediction of the average temperature of Banyuwangi Regency is needed. This research used secondary data from the official website of the Central Statistics Agency (BPS) of Banyuwangi Regency per month from January 2012 to December 2023. Predictions are made using the seasonal autoregressive integrated moving average (SARIMA) approach. The best model is selected based on its fulfillment of stationarity, the significance of its parameters, and compliance with the assumptions of normality and white noise. From this method, the best model obtained to predict the average temperature of Banyuwangi Regency is the probabilistic SARIMA (1,0,0)(0,1,1)12. The probabilistic SARIMA model treats both parameters and forecasts as probability distributions. The average temperature of Banyuwangi Regency is obtained for the next year, namely from January 2023 to December 2023, with a MAPE of 1.63%. With an accuracy rate of 98.37%, it can be said that the probabilistic SARIMA (1,0,0)(0,1,1)12 model is accurate in predicting the average temperature of Banyuwangi Regency in the future. Thus, the prediction of the average temperature of Banyuwangi Regency is expected to help the community and government manage the impact of erratic climate change to improve the welfare of all Banyuwangi people.

BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPANVol. 19(3)
Universitas Airlangga (ID)
Openalex Percentile: Top 77%
Data Mining and Machine Learning Applications
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PREDICTION OF AVERAGE TEMPERATURE IN BANYUWANGI REGENCY USING SARIMA — Sediono Sediono, Idrus Syahzaqi, et al. · BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN (2025) | TGRS Research Map | TGRS