Skripsi

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

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507004103	T178741	T1787412025	Central Library (REFERENCE)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1787412025

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xvi, 98 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem komputer

Specific Detail Info

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Statement of Responsibility

TUTI

Other version/related

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