PREDIKSI PENGISIAN DAYA POWER SUPPLY DARI SOLAR CELL MENGGUNAKAN ALGORITMA REGRESI LINEAR

RAHARJO, JOHAN SUGIARTO and Ubaya, Huda and Sutarno, Sutarno (2025) PREDIKSI PENGISIAN DAYA POWER SUPPLY DARI SOLAR CELL MENGGUNAKAN ALGORITMA REGRESI LINEAR. Undergraduate thesis, Sriwijaya University.

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Abstract

This study aims to evaluate the performance of a solar power generation system in producing electrical energy and its capability to meet the energy demands of a smart home. The methodology involves data exploration, predictive modeling using linear regression, and energy sufficiency analysis. Preprocessing results indicate that the dataset is clean and suitable for analysis. Exploratory analysis reveals daily power fluctuations influenced by solar irradiation and performance differences between plants. The linear regression model shows that variables such as DC Power, Daily Yield, Module Temperature, Ambient Temperature, and Irradiation significantly affect AC Power predictions. Model evaluation produced an R² score of 0.9060 and a MAPE of 5.49%, indicating high prediction accuracy. Energy sufficiency analysis confirms that the 2 MWp solar power system is fully capable of meeting the energy needs of a smart home during a 45-day observation period. With an average energy production of 20,002 kWh and a maximum household consumption of 4,035 kWh, the system effectively supports continuous smart home operation without energy deficits.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Energi surya, smart home, regresi linier, prediksi daya, evaluasi energi.
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	johan sugiarto raharjo
Date Deposited:	16 Jul 2025 02:04
Last Modified:	16 Jul 2025 02:04
URI:	http://repository.unsri.ac.id/id/eprint/178741

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