Peramalan Beban Listrik Kabupaten Pesisir Selatan Dengan Analisis Regresi

The more electric vehicles emerge, the more electricity demand will increase in each region. This will encourage electricity providers to increase the number or capacity of generators. The construction of a new power plant requires load forecasting to determine how much capacity the plant will build...

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Main Authors: Zulka Hendri, Efendi Efendi, Junaidi Asrul, Fitriadi Fitriadi
Format: Article
Language:Indonesian
Published: Jurusan Teknik Elektro Politeknik Negeri Padang 2023-06-01
Series:Elektron
Subjects:
Online Access:https://jie.pnp.ac.id/index.php/jie/article/view/340
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author Zulka Hendri
Efendi Efendi
Junaidi Asrul
Fitriadi Fitriadi
author_facet Zulka Hendri
Efendi Efendi
Junaidi Asrul
Fitriadi Fitriadi
author_sort Zulka Hendri
collection DOAJ
description The more electric vehicles emerge, the more electricity demand will increase in each region. This will encourage electricity providers to increase the number or capacity of generators. The construction of a new power plant requires load forecasting to determine how much capacity the plant will build. This study aims to predict the electrical load in Pesisir Selatan, West Sumatra until 2031 using linear regression analysis and time series. Forecasting is done on each sector of PLN customers. Forecasting is done based on the PLN customer sector. The forecasting sectors are the household, business, social and government sectors. The four test criteria were carried out are namely the coefficient of determination test (R2), the F test, the T test and the mean absolute percentage error (MAPE). The forecasting results show that in 2031 the electricity load for the household sector is 120.1 MW, the business sector is 5.7 MW, the social sector is 56.9 MW and the government is 9.5 MW.
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spelling doaj.art-8800c2be8dc94a1a8272afda5761a56b2023-11-30T04:09:28ZindJurusan Teknik Elektro Politeknik Negeri PadangElektron2085-69892654-47332023-06-0171210.30630/eji.15.1.340340Peramalan Beban Listrik Kabupaten Pesisir Selatan Dengan Analisis RegresiZulka Hendri0Efendi Efendi1Junaidi Asrul2Fitriadi Fitriadi3Politeknik Negeri PadangPoliteknik Negeri PadangPoliteknik Negeri PadangPoliteknik Negeri PadangThe more electric vehicles emerge, the more electricity demand will increase in each region. This will encourage electricity providers to increase the number or capacity of generators. The construction of a new power plant requires load forecasting to determine how much capacity the plant will build. This study aims to predict the electrical load in Pesisir Selatan, West Sumatra until 2031 using linear regression analysis and time series. Forecasting is done on each sector of PLN customers. Forecasting is done based on the PLN customer sector. The forecasting sectors are the household, business, social and government sectors. The four test criteria were carried out are namely the coefficient of determination test (R2), the F test, the T test and the mean absolute percentage error (MAPE). The forecasting results show that in 2031 the electricity load for the household sector is 120.1 MW, the business sector is 5.7 MW, the social sector is 56.9 MW and the government is 9.5 MW.https://jie.pnp.ac.id/index.php/jie/article/view/340multiple linear regression analysis, r2, f test, t test and mape.
spellingShingle Zulka Hendri
Efendi Efendi
Junaidi Asrul
Fitriadi Fitriadi
Peramalan Beban Listrik Kabupaten Pesisir Selatan Dengan Analisis Regresi
Elektron
multiple linear regression analysis, r2, f test, t test and mape.
title Peramalan Beban Listrik Kabupaten Pesisir Selatan Dengan Analisis Regresi
title_full Peramalan Beban Listrik Kabupaten Pesisir Selatan Dengan Analisis Regresi
title_fullStr Peramalan Beban Listrik Kabupaten Pesisir Selatan Dengan Analisis Regresi
title_full_unstemmed Peramalan Beban Listrik Kabupaten Pesisir Selatan Dengan Analisis Regresi
title_short Peramalan Beban Listrik Kabupaten Pesisir Selatan Dengan Analisis Regresi
title_sort peramalan beban listrik kabupaten pesisir selatan dengan analisis regresi
topic multiple linear regression analysis, r2, f test, t test and mape.
url https://jie.pnp.ac.id/index.php/jie/article/view/340
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AT efendiefendi peramalanbebanlistrikkabupatenpesisirselatandengananalisisregresi
AT junaidiasrul peramalanbebanlistrikkabupatenpesisirselatandengananalisisregresi
AT fitriadifitriadi peramalanbebanlistrikkabupatenpesisirselatandengananalisisregresi