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dc.contributor.advisorHarahap, Raja
dc.contributor.authorPurba, Samuel Patra
dc.date.accessioned2025-07-25T02:26:58Z
dc.date.available2025-07-25T02:26:58Z
dc.date.issued2025
dc.identifier.urihttps://repositori.usu.ac.id/handle/123456789/107377
dc.description.abstractThis study focuses on long-term electricity load forecasting at the end of the year using the linear regression method, applied to the Glugur Substation in Medan. Historical load data from 2021 to 2024 was used as the foundation to forecast electrical loads through the end of 2026. The forecasting process models the relationship between the progression of time and peak load/energy usage using a linear regression approach. The forecasting results demonstrate a consistent and stable upward trend in load demand. Model accuracy was evaluated using MAPE, R², MAE, and RMSE metrics. The lowest MAPE value of 1.37% was achieved at the Selayang Substation, while the Glugur Substation yielded a MAPE of 2.43%, indicating good accuracy for long-term forecasting. This research contributes to enhancing the reliability and efficiency of power distribution system planningen_US
dc.language.isoiden_US
dc.publisherUniversitas Sumatera Utaraen_US
dc.subjectPeramalan beban listriken_US
dc.subjectregresi linieren_US
dc.subjectGardu Induk Gluguren_US
dc.subjectMAPEen_US
dc.subjectsistem distribusi tenaga listriken_US
dc.subjectbeban puncaken_US
dc.subjectdata historisen_US
dc.titlePeramalan Beban Jangka Panjang pada Akhir Tahun Menggunakan Metode Regresi Linearen_US
dc.title.alternativeLong-Term Expense Forecasting at the End of the Year Using the Linear Regression Methoden_US
dc.typeThesisen_US
dc.identifier.nimNIM190402126
dc.identifier.nidnNIDN0013016503
dc.identifier.kodeprodiKODEPRODI20101#Teknik Elektro
dc.description.pages84 pagesen_US
dc.description.typeSkripsi Sarjanaen_US
dc.subject.sdgsSDGs 4. Quality Educationen_US


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