STUDI PERKIRAAN KEBUTUHAN ENERGI LISTRIK PELANGGAN

DI PT.PLN (Persero) UNIT LAYANAN PELANGGAN ABEPURA

Authors

  • Marianus Ile Koten Universitas Cenderawasih
  • Dultudes Mangopo Universitas Cenderawasih
  • Moh. Arie Reza Universitas Cenderawasih
  • Marthen Liga Universitas Cenderawasih
  • Afner S Sinaga Universitas Cenderawasih
  • Suparno Universitas Cenderawasih

Keywords:

Forecasting Electrical Energy Needs, Multiple Linear Regression

Abstract

Electrical energy is one of the important needs for the population. Almost all the activities we do use electrical energy, both in household activities and industrial activities. The need for electrical energy will increase every year. So, predictions are needed to find out the electrical energy that will be needed. Electricity forecasting is a method used to calculate the level of electrical energy demand in the future and is expressed in a mathematical model. To predict electrical energy needs at ULP Abepura, researchers used the multiple linear regression method. The research that has been carried out has produced several results. The prediction of electrical energy needs from 2023 to 2027 in the Abepura Customer Service Unit (ULP) area has increased from 2023 to 2027 with the lowest amount of electrical energy needed in 2023 with a value of 23,215,634 kWh. and the highest need for electrical energy will be in 2027 with a value of 30,233,344 kWh. It is hoped that in the future there will be a need to increase electrical power in the Abepura Customer Service Unit (ULP). Due to the increase in population.

References

Fisika, J., Matematika, F., Ilmu, D., Alam, P., & Udayana, U. (2016). Regresi linier sederhana.

Fisika, J., & Udayana, U. (2016). Regresi linier berganda.

Harlan, J. (n.d.). peramalan energi listrik.

Hidayati, D. N. U. R., Studi, P., Elektro, T., Teknik, F., & Surakarta, U. M. (2018). Perkiraan Kebutuhan Konsumsi Energi Listrik Di Kabupaten Pati Pada Tahun 2026 Dengan Menggunakan.

Ii, B. A. B., & Pustaka, T. (2007). No Title. 8–32.

Junaidi, J. (2014). Regresi dengan Microsoft Office Excel. 1–12.

Kastanja, A. J., & Tupalessy, J. (2022). Jurnal simetrik vol.7, no.1, juni 2017. 7(1), 41–46.

Kurniawan, D. (2008). Regresi linier.

Panduan, B., & Komputer, B. (n.d.). Belajar Microsoft Excel.

Rahmi, N., Cahayahati, I., & Elektro, J. T. (2021). Studi Perkiraan Kebutuhan Energi Listrik Dengan Metoda Regresi Linear Berganda Pada Kota Padang Panjang Tahun 2021-2030.

Syafruddin, M., Hakim, L., & Despa, D. (n.d.). Metode Regresi Linier untuk Prediksi KebutuhanEnergi Listrik Jangka Panjang ( Studi Kasus Provinsi Lampung ). 1.

Taufik, I. (2022). Analisis Peramalan Kebutuhan Energi Listrik Unit Layanan Pelanggan ( Ulp ) Rimbo Bujang

Downloads

Published

2024-03-03

How to Cite

Marianus Ile, K., Mangopo, D., Reza, M. A., Liga, M., Sinaga, A. S., & Suparno, S. (2024). STUDI PERKIRAAN KEBUTUHAN ENERGI LISTRIK PELANGGAN: DI PT.PLN (Persero) UNIT LAYANAN PELANGGAN ABEPURA. Jurnal Teletronic, 1(3), 11–16. Retrieved from http://teletronic.elektrouncen.com/index.php/teletronic/article/view/57

Issue

Vol. 1 No. 3 (2024): Maret

Section

Articles

License

Copyright (c) 2024 Jurnal teletronic

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Most read articles by the same author(s)

1 2 > >>