Azalia, Irmanita (2016) Peramalan Kebutuhan Energi Listrik Bulanan Di Gresik, Jawa Timur Menggunakan Metode Autoregressive Integrated Moving Average, Adaptive Neuro Fuzzy Inference System Dan Fungsi Transfer. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Peningkatan jumlah pelanggan listrik tiap tahunnya di
Indonesia mengakibatkan kebutuhan energi listrik juga terus
meningkat sehingga PT. PLN (Persero) harus dapat
memperkirakan kapasitas pembangkit listrik yang dibutuhkan di
Indonesia untuk jangka waktu ke depan, maka diperlukan
peramalan konsumsi listrik agar kebutuhan pelanggan listrik
terpenuhi. Sehingga pada penelitian dilakukan peramalan
konsumsi listrik pada lima sektor, yaitu sektor sosial, rumah
tangga, bisnis, industri, dan publik menggunakan metode
peramalan ARIMA dan ANFIS. Selain itu, digunakan metode
fungsi transfer untuk mengetahui pengaruh jumlah pelanggan
listrik terhadap konsumsi listrik. Hasil yang diperoleh dari
penelitian ini bahwa metode peramalan dengan ARIMA pada
konsumsi listrik tiap sektor menghasilkan nilai error ramalan
yang lebih baik bila dibandingkan dengan metode ANFIS. Pada
metode fungsi transfer diperoleh model pada masing-masing
sektor sehingga dapat dikatakan bahwa jumlah pelanggan
berpengaruh terhadap peramalan jumlah konsumsi listrik pada
masing-masing sektor.
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The number of customers of the electricity increases
remarkably every year; consequently, demands over electricity
power also subsequently increase. Pertinent to this, PT. PLN
(Persero) has to be able to forecast the capacities of needed
power plants for the coming years or decades; therefore,
forecasting over the consumptions of the electricity needs to be
made to meet the customer’s demands. In this present research,
forecasting over electricity consumption is made covering five
demands, namely social, domestic, business, industry, and public.
This employs ARIMA and ANFIS forecasting method; besides that
function transfer method is also used to figure out the effects of
the customers numbers over the uses of electricity. The finding of
the present research would reveal that forecasting method using
ARIMA over the consumption of electricity in each domain would
yield error values better than that of using ANFIS method. The,
function transfer method would lead to each model for each
domain so it can be inferred that numbers of customers would
affect forecasting over consumptions of electricity in each
domain.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSt 519.536 Aza p |
| Uncontrolled Keywords: | ANFIS, ARIMA, Fungsi Transfer, Peramalan, Konsumsi Listrik, Jumlah Pelanggan Listrik. |
| Subjects: | H Social Sciences > HA Statistics |
| Divisions: | Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Users 13 not found. |
| Date Deposited: | 12 Jun 2017 06:34 |
| Last Modified: | 26 Dec 2018 06:43 |
| URI: | http://repository.its.ac.id/id/eprint/41600 |
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