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MODELING THE INFLUENCE OF CRUDE OIL PRODUCTION AGAINST INDONESIAN SOLAR WHOLESALE PRICE INDEX WITH LEAST SQUARE SPLINE ESTIMATOR APPROACH

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 19 No. 2 (2025) · hlm. 805–818

DOI
10.30598/barekengvol19iss2pp805-818
ISSN
2615-3017, 1978-7227
Terbit
2025-04-01
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Solar plays a crucial role in supporting energy sector activities in Indonesia. The fluctuating price of solar is influenced by crude oil production, as crude oil is the main raw material in solar production. The Russia-Ukraine war, which reached its peak in March 2020, also impacted global oil production, given that Russia is one of the largest oil producers and exporters in the world. This study aims to model the effect of crude oil production on the Solar Wholesale Price Index (SWPI) in Indonesia after the Russia-Ukraine war using the Least Squares Spline estimator approach. This approach was chosen because the relationship between the variables is complex and nonlinear, making linear models unsuitable. The results show that the best model is a nonparametric model with three knot points at a polynomial degree of one, which explains 90.26% of the variability in crude oil production relative to the SWPI. The optimal knot points were selected using the Generalized Cross Validation (GCV) method, resulting in a minimum GCV value of 320.9889. Crude oil production was found to have a significant effect on the SWPI and meets the classical assumption tests. However, this study has limitations, as it only considers the effect of crude oil production without including other external factors, such as energy policies or geopolitical influences. Additionally, the model still has limitations in capturing more complex relationship patterns. This study offers an original contribution through the application of the Least Squares Spline estimator approach, which has not been widely used before in analyzing the relationship between crude oil production and SWPI in Indonesia. For future research, it is recommended that the model be expanded by considering more knot points and higher polynomial degrees to capture more complex relationship patterns between these variables.

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Rekan penulisOrganisasiArtikel bersama
Suliyanto SuliyantoUniversitas Airlangga4
Najwa Khoir AldawiyahUniversitas Airlangga3
Nur ChamidahUniversitas Airlangga2
Ardi KurniawanUniversitas Airlangga2
Elly AnaUniversitas Airlangga2
Suliyanto SuliyantoUniversitas Airlangga2
Anisah Nabilah GhasaniUniversitas Airlangga2
Muhammad Fariz Fadillah MardiantoUniversitas Airlangga2
Berliani LarasatiUniversitas Airlangga1
Qumadha Zaenal AbidinAfiliasi tidak diketahui1
Juan Krisfigo PrasetyoUniversitas Airlangga1
Alma Khalisa RahmaUniversitas Airlangga1
Steven SoewignjoUniversitas Airlangga1
Ni Wayan Widya Septia SariUniversitas Airlangga1
Andini Putri MedianiUniversitas Airlangga1
M. Aqil Zaidan KamilUniversitas Airlangga1
Galuh Cahya NugrahaUniversitas Airlangga1
Billy Christandy SuyonoUniversitas Airlangga1
Idrus SyahzaqiUniversitas Airlangga1
Muhammad Rosyid Ridho Az ZuhroUniversitas Airlangga1
Sediono SedionoUniversitas Airlangga1
Tentri Ryan RahmanitaUniversitas Airlangga1
Kimberly Maserati SiagianUniversitas Airlangga1
Nadinta Kasih AmaliaUniversitas Airlangga1
Nadya Lovita Hana TrisaUniversitas Airlangga1
Gabriella Agnes BudijonoUniversitas Airlangga1
Rere Fetri DamanikUniversitas Airlangga1
Azizah Atsariyyah ZhafiraUniversitas Airlangga1
Dita AmeliaAfiliasi tidak diketahui1
M. Fariz Fadillah MardiantoAfiliasi tidak diketahui1
Elly AnaAfiliasi tidak diketahui1
Aini Divayanti ArrofahAfiliasi tidak diketahui1
Azzah Nazhifa Wina RamadhaniAfiliasi tidak diketahui1
Aulia RamadhantiAfiliasi tidak diketahui1
M. Nabil SaputraUniversitas 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)
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	<dc:title xml:lang="en-US">MODELING THE INFLUENCE OF CRUDE OIL PRODUCTION AGAINST INDONESIAN SOLAR WHOLESALE PRICE INDEX WITH LEAST SQUARE SPLINE ESTIMATOR APPROACH</dc:title>
	<dc:creator>Pratiwi, Rosidun Nindyo</dc:creator>
	<dc:creator>Fauziah, Nathania</dc:creator>
	<dc:creator>Syahputra, Bimo Okta</dc:creator>
	<dc:creator>Firmanda, Ahmad Wahyu</dc:creator>
	<dc:creator>Amelia, Dita</dc:creator>
	<dc:description xml:lang="en-US">Solar plays a crucial role in supporting energy sector activities in Indonesia. The fluctuating price of solar is influenced by crude oil production, as crude oil is the main raw material in solar production. The Russia-Ukraine war, which reached its peak in March 2020, also impacted global oil production, given that Russia is one of the largest oil producers and exporters in the world. This study aims to model the effect of crude oil production on the Solar Wholesale Price Index (SWPI) in Indonesia after the Russia-Ukraine war using the Least Squares Spline estimator approach. This approach was chosen because the relationship between the variables is complex and nonlinear, making linear models unsuitable. The results show that the best model is a nonparametric model with three knot points at a polynomial degree of one, which explains 90.26% of the variability in crude oil production relative to the SWPI. The optimal knot points were selected using the Generalized Cross Validation (GCV) method, resulting in a minimum GCV value of 320.9889. Crude oil production was found to have a significant effect on the SWPI and meets the classical assumption tests. However, this study has limitations, as it only considers the effect of crude oil production without including other external factors, such as energy policies or geopolitical influences. Additionally, the model still has limitations in capturing more complex relationship patterns. This study offers an original contribution through the application of the Least Squares Spline estimator approach, which has not been widely used before in analyzing the relationship between crude oil production and SWPI in Indonesia. For future research, it is recommended that the model be expanded by considering more knot points and higher polynomial degrees to capture more complex relationship patterns between these variables.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2025-04-01</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/14292</dc:identifier>
	<dc:identifier>10.30598/barekengvol19iss2pp805-818</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application; 805-818</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol19iss2year2025</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14292/9900</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Rosidun Nindyo Pratiwi, Nathania Fauziah, Bimo Okta Syahputra, Ahmad Wahyu Firmanda, Dita Amelia</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>