IMPLEMENTASI METODE EXPONENTIAL SMOOTHING UNTUK
PRAKIRAAN KEBUTUHAN PELANGGAN INDUSTRI DI PT. PLN
(PERSERO) UP3 SURABAYA BARAT BERBASIS WEB
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Chameliana, Tirta Hayu
Luqman, Luqman
Kuswardani, Dwina
Luqman, Luqman
Kuswardani, Dwina
Subject
Teknik Informatika
Datestamp
2023-06-21 03:10:50
Abstract :
The industrial sector is the sector with the largest electricity consumption every day. PT. PLN (Persero) UP3 Surabaya Barat has difficulties in providing the appropriate electricity usage needs for the next period. The need for a system that can predict electricity consumption, especially the industrial sector for the next period. Therefore, this study proposes the development of a prediction system for industrial customer needs at PT. PLN (Persero) UP3 Surabaya Barat. Industrial customer data is processed using the Single Exponential Smoothing method, which is then displayed on a website. Industrial customer data from January 2018 to May 2022 was processed to obtain a prediction of industrial electricity use in June 2022. The evaluation of the prediction results stated that alpha = 0.9 resulted in the smallest error value with MAPE = 26.85% and predicted industrial electricity consumption in June 2022 of 206.729 kWh. It can be concluded that the predictions obtained using the Single Exponential Smoothing method on electricity consumption in the industrial sector produce a good evaluation level with a relatively small error percentage.
The industrial sector is the sector with the largest electricity consumption every day. PT. PLN (Persero) UP3 Surabaya Barat has difficulties in providing the appropriate electricity usage needs for the next period. The need for a system that can predict electricity consumption, especially the industrial sector for the next period. Therefore, this study proposes the development of a prediction system for industrial customer needs at PT. PLN (Persero) UP3 Surabaya Barat. Industrial customer data is processed using the Single Exponential Smoothing method, which is then displayed on a website. Industrial customer data from January 2018 to May 2022 was processed to obtain a prediction of industrial electricity use in June 2022. The evaluation of the prediction results stated that alpha = 0.9 resulted in the smallest error value with MAPE = 26.85% and predicted industrial electricity consumption in June 2022 of 206.729 kWh. It can be concluded that the predictions obtained using the Single Exponential Smoothing method on electricity consumption in the industrial sector produce a good evaluation level with a relatively small error percentage.
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