Melola Discovery

← Melola Discovery

Akses terbuka Jurnal SINTA 3

PREDICTION OF AVERAGE TEMPERATURE IN BANYUWANGI REGENCY USING SARIMA

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 19 No. 3 (2025) · hlm. 2207–2218

DOI
10.30598/barekengvol19iss3pp2207-2218
ISSN
2615-3017, 1978-7227
Terbit
2025-07-01
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

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.

Jaringan kolaborasi para penulis

27 penulis · 72 tautan kepenulisan bersama · 4 lintas organisasi

Arahkan kursor atau ketuk sebuah nama untuk menyorot rekan penulisnya. Klik dua kali untuk membuka halaman penulis.

  • Universitas Airlangga
  • Institut Teknologi Sepuluh Nopember
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
  • Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Dita AmeliaUniversitas Airlangga4
Aurellia Calista AnggakusumaUniversitas Airlangga2
Ezha Easyfa WieldyanisaUniversitas Airlangga2
Sabrina Salsa OktaviaUniversitas Airlangga2
Ardi KurniawanUniversitas Airlangga2
Heri KuswantoInstitut Teknologi Sepuluh Nopember1
Idrus SyahzaqiInstitut Teknologi Sepuluh Nopember1
Magdalena EffendiInstitut Teknologi Sepuluh Nopember1
Hasri RahmawatiInstitut Teknologi Sepuluh Nopember1
Toha SaifudinUniversitas Airlangga1
Maria Setya DewantiUniversitas Airlangga1
Aurelia Islami AzisUniversitas Airlangga1
Muhammad Rosyid Ridho Az ZuhroUniversitas Airlangga1
Tentri Ryan RahmanitaUniversitas Airlangga1
Elly AnaUniversitas Airlangga1
Nuzulia AnidaUniversitas Airlangga1
Nabila Angel NafishaUniversitas Airlangga1
Suliyanto SuliyantoUniversitas Airlangga1
Nike Meliana RahmawatiUniversitas Airlangga1
Dwi Syarifatun Nisya’Afiliasi tidak diketahui1
Dinda Rahma AlyaUniversitas Airlangga1
Salsabilla Rusydah PutriUniversitas Airlangga1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">PREDICTION OF AVERAGE TEMPERATURE IN BANYUWANGI REGENCY USING SARIMA</dc:title>
	<dc:creator>Syahzaqi, Idrus</dc:creator>
	<dc:creator>Sediono, Sediono</dc:creator>
	<dc:creator>Dyaksa, Mega Kurnia</dc:creator>
	<dc:creator>Vionita, Anggi Triya</dc:creator>
	<dc:creator>Ghasani, Anisah Nabilah</dc:creator>
	<dc:description xml:lang="en-US">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.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2025-07-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/17469</dc:identifier>
	<dc:identifier>10.30598/barekengvol19iss3pp2207-2218</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application; 2207-2218</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol19iss3year2025</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/17469/10807</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Idrus Syahzaqi, Sediono Sediono, Mega Kurnia Dyaksa, Anggi Triya Vionita, Anisah Nabilah Ghasani</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>