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Pengaruh Sudut Kemiringan Dan Intensitas Matahari Terhadap Karakteristik Modul Polycristaline Dengan Metode Regresi Berganda

Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) · Vol. 6 No. 3 (2021) · hlm. 171–175

DOI
10.33772/jfe.v6i3.19844
ISSN
2502-5562
Terbit
2021-08-30
Penerbit
Universitas Halu Oleo
Bahasa
eng
Lisensi
creativecommons.org/licenses/by/4.0

Abstrak

Solar energy is often known by other terms solar energy is a form of renewable energy source. The potential of solar energy certainly affects the power generated in solar modules, there are several influences that cause solar energy not to be obtained optimally. In this study will be made mathematical modeling using multiple regression methods exposed to the angle of tilt and intensity of the sun with the research object of the polycristalline type solar module. The results obtained by calculating mathematically obtained the accuracy of the model with MAPE, as well as the adjusted value of R square of 0.960363563 which states that the percentage of the influence of irradiation-free variables and temperature simultaneously on the current obtained is very strong. While the results of calculations with double linear regression, the value of the regression coefficient on the irradiation variable (x_1) by 0.0000316, it means that if other variables remain and irradiation variables increase by 100 W/m2, then the current increases by 0.00316 A. Then the regression coefficient on the temperature variable (x_2) by 0.010573, this means if other variables remain and temperature variables increase by 1oC, then the current increases by 0.010573 A. From these results, it should be known the level of accuracy of the model which in this case uses MAPE. MAPE obtained on this model is 7.046%, this corresponds to the error standard of 0.007650294 with an average current measurement scale of ±0.1 A. Thus, the MAPE results show that the model has an accuracy of 92.954%, which means that the modeling obtained is very good.

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Sumber metadata: OAI-PMH (metadata jurnal) https://ojs.uho.ac.id/index.php/JFE/oai, pertama di-harvest 31 Okt 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">Pengaruh Sudut Kemiringan Dan Intensitas Matahari Terhadap Karakteristik Modul Polycristaline Dengan Metode Regresi Berganda</dc:title>
	<dc:creator>Samsurizal, Samsurizal</dc:creator>
	<dc:creator>Fikri, Miftahul</dc:creator>
	<dc:creator>Makkulau, Andi</dc:creator>
	<dc:creator>Christiono, Chistiono</dc:creator>
	<dc:subject xml:lang="en-US">Solar Energy, Tilt Angle, Polycristaline, Current, Multiple Regression.</dc:subject>
	<dc:description xml:lang="en-US">Solar energy is often known by other terms solar energy is a form of renewable energy source. The potential of solar energy certainly affects the power generated in solar modules, there are several influences that cause solar energy not to be obtained optimally. In this study will be made mathematical modeling using multiple regression methods exposed to the angle of tilt and intensity of the sun with the research object of the polycristalline type solar module. The results obtained by calculating mathematically obtained the accuracy of the model with MAPE, as well as the adjusted value of R square of 0.960363563 which states that the percentage of the influence of irradiation-free variables and temperature simultaneously on the current obtained is very strong. While the results of calculations with double linear regression, the value of the regression coefficient on the irradiation variable (x_1) by 0.0000316, it means that if other variables remain and irradiation variables increase by 100 W/m2, then the current increases by 0.00316 A. Then the regression coefficient on the temperature variable (x_2) by 0.010573, this means if other variables remain and temperature variables increase by 1oC, then the current increases by 0.010573 A. From these results, it should be known the level of accuracy of the model which in this case uses MAPE. MAPE obtained on this model is 7.046%, this corresponds to the error standard of 0.007650294 with an average current measurement scale of ±0.1 A. Thus, the MAPE results show that the model has an accuracy of 92.954%, which means that the modeling obtained is very good.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Halu Oleo</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2021-08-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs.uho.ac.id/index.php/JFE/article/view/19844</dc:identifier>
	<dc:identifier>10.33772/jfe.v6i3.19844</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali); Vol 6, No 3 (2021): Jurnal Elektroda Vol 6 No 3; 171-175</dc:source>
	<dc:source>2502-5562</dc:source>
	<dc:source>10.33772/jfe.v6i3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs.uho.ac.id/index.php/JFE/article/view/19844/pdf</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 Samsurizal Samsurizal, Miftahul Fikri, Andi Makkulau, Chistiono Christiono</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>