Characterization of Daily Solar Radiation Intensity Based on In-Situ Data Using the BH1750 Sensor

Pebralia, Jesi; Fendriani, Yoza; Afrianto, M. Ficky; Deswardani, Frastica; Alrizal, Alrizal

doi:10.22437/proca.v2i2.55521

Akses terbuka Jurnal

Characterization of Daily Solar Radiation Intensity Based on In-Situ Data Using the BH1750 Sensor

Proceedings Academic Universitas Jambi · Vol. 2 No. 2 (2026) · hlm. 87–92

DOI: 10.22437/proca.v2i2.55521
Terbit: 2026-07-15
Penerbit: LPPM Universitas Jambi
Bahasa: en
Lisensi: creativecommons.org/licenses/by/4.0

Abstrak

This study aims to characterize the daily solar radiation intensity using in-situ data obtained from the BH1750 sensor. The measurement system was designed using the BH1750 light sensor, with data transmitted wirelessly to the ThingSpeak cloud platform for storage and analysis. Data collection was carried out over two consecutive days in an open area with a recording interval of one hour. The measurement results show that the intensity pattern on the first day reached its peak (approximately 62 kLx) at 12:00 noon. This pattern exhibits a nearly symmetric distribution, representing relatively clear and stable weather conditions around midday. In contrast, the second day’s peak intensity (around 65 kLx) occurred earlier, at 11:00, and rose again at 13:00, indicating sharp intensity fluctuations. These fluctuations resulted in two distinct local peaks before the intensity declined to zero at sunset. The differences in peak timing and daily fluctuation patterns highlight the need for further analysis using machine learning approaches to accurately model the complex and non-linear relationships within solar radiation data.

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Diponegoro University
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Rekan penulis	Organisasi	Artikel bersama
Febri Berthalita Pujaningsih	Afiliasi tidak diketahui	2
Lucky Zaehir Maulana	Afiliasi tidak diketahui	2
Rista Mutia Anggraini	Afiliasi tidak diketahui	2
Muhammad Ficky Afrianto	Afiliasi tidak diketahui	2
R Angelina	Afiliasi tidak diketahui	1
Samsisar	Afiliasi tidak diketahui	1
Ichy Lucya Resta	Afiliasi tidak diketahui	1
Willy Bima Alfajri	Diponegoro University	1
Fiqri Al Faruqi	Afiliasi tidak diketahui	1
V. A Nanda	Afiliasi tidak diketahui	1
Alrizal	Afiliasi tidak diketahui	1

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Sumber metadata: OAI-PMH (metadata jurnal) https://online-journal.unja.ac.id/index.php/PROCA/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.

Metadata asli (oai_dc)

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	<dc:title xml:lang="en">Characterization of Daily Solar Radiation Intensity Based on In-Situ Data Using the BH1750 Sensor</dc:title>
	<dc:creator xml:lang="en">Pebralia, Jesi</dc:creator>
	<dc:creator xml:lang="en">Fendriani, Yoza</dc:creator>
	<dc:creator xml:lang="en">Afrianto, M. Ficky</dc:creator>
	<dc:creator xml:lang="en">Deswardani, Frastica</dc:creator>
	<dc:creator xml:lang="en">Alrizal, Alrizal</dc:creator>
	<dc:subject xml:lang="en">Radiation intensity</dc:subject>
	<dc:subject xml:lang="en">Sensor BH1750</dc:subject>
	<dc:subject xml:lang="en">Machine learning</dc:subject>
	<dc:description xml:lang="en">This study aims to characterize the daily solar radiation intensity using in-situ data obtained from the BH1750 sensor. The measurement system was designed using the BH1750 light sensor, with data transmitted wirelessly to the ThingSpeak cloud platform for storage and analysis. Data collection was carried out over two consecutive days in an open area with a recording interval of one hour. The measurement results show that the intensity pattern on the first day reached its peak (approximately 62 kLx) at 12:00 noon. This pattern exhibits a nearly symmetric distribution, representing relatively clear and stable weather conditions around midday. In contrast, the second day’s peak intensity (around 65 kLx) occurred earlier, at 11:00, and rose again at 13:00, indicating sharp intensity fluctuations. These fluctuations resulted in two distinct local peaks before the intensity declined to zero at sunset. The differences in peak timing and daily fluctuation patterns highlight the need for further analysis using machine learning approaches to accurately model the complex and non-linear relationships within solar radiation data.</dc:description>
	<dc:publisher xml:lang="en">LPPM Universitas Jambi</dc:publisher>
	<dc:date>2026-07-15</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://online-journal.unja.ac.id/PROCA/article/view/55521</dc:identifier>
	<dc:identifier>10.22437/proca.v2i2.55521</dc:identifier>
	<dc:source xml:lang="en">Proceedings Academic Universitas Jambi; Vol. 2 No. 2 (2026): The 3rd Jambi International Conference On Engineering, Science and Technology (JICEST); 87-92</dc:source>
	<dc:source>10.22437/proca.v2i2</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://online-journal.unja.ac.id/PROCA/article/view/55521/24947</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2026 Jesi Pebralia, Yoza Fendriani, M. Ficky Afrianto, Frastica Deswardani, Alrizal</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
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