Widyandari L W, Trigati (2015) Peramalan Harga Minyak Mentah Di Indonesia Dengan Menggunakan Metode Fuzzy Time Series. Undergraduate thesis, Institut Technology Sepuluh Nopember.
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Abstract
Meramalkan pergerakan harga minyak sangat penting bagi pelaku
bisnis dalam pasar energy. Hal ini dikarenakan minyak bumi
merupakan input vital dalam proses produksi industri, terutama
untuk menghasilkan listrik, menjalankan mesin produksi dan
mengangkut hasil produksi ke pasar. Mengingat peranannya yang
vital tersebut, maka dampak yang timbul akibat fluktuasi harga
minyak akan berpengaruh terhadap bidang lain, diantaranya
pertumbuhan ekonomi, laju inflasi, jumlah uang beredar, nilai tukar
riil rupiah terhadap US dolar dan suku bunga.Data harga minyak
mentah Indonesia merupakan data time series. Dikatakan time series
dikarenakan data harga minyak mempunyai interval waktu yang
sama dan diamati pada suatu periode tertentu. Selain itu data harga
minyak memiliki subjektivitas terhadap pengkategorian harga
minyak. Subjektivitas terhadap harga minyak merupakan nilai
linguistik. Oleh sebab itu, dibutuhkan proses peramalan dengan
mengkaitkan time series dan teori fuzzy. Sehingga pada penelitian
ini akan dikembangkan metode Fuzzy Time Series Markov Chain
Model untuk meramalkan harga minyak mentah Indonesia. Fuzzy
time series menggabungkan sikap subjektif orang dan nilai-nilai
obyektif historis dapat membantu memecahkan masalah peramalan.
Dalam penelitian ini, data yang digunakan adalah data harian
harga minyak mentah Indonesia dari tahun 2010 hingga 2014.
Analisa model peramalan yang sesuai dengan harga minyak mentah
Indonesia dimana selama ini selalu mengalami fluktuasi dilakukan
dengan pengujian proporsi data, pengujian kinerja model, serta
pengujian perbandingan peramalan dengan metode FTS Markov
Chain dengan FTS biasa. Hasil pengujian menunjukkan bahwa model peramalan yang tepat
untuk data harga minyak mentah Indonesia adalah dengan
menggunakan metode peramalan Fuzzy Time Series Markov Chain
Model, dengan proporsi data 70:30, yang menghasilkan eror MAPE
SLC sebesar 2.35%, Arjuna 2.53%, Attaka 2.22%, Cinta 2.59%,
Duri 2.44%, Widuri 2.56%, Belida 2.45%, dan Senipah Condensate
sebesar 2.36%.
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Forecasting the movement of oil prices is very important for
businessmen in the energy market. This is because oil is a vital
input in the process of industrial production, mainly to
generate electricity, run the machine production and
transporting produce to market. Considering the vital role
these impacts caused by fluctuations in oil prices will affect
other fields, such as economic growth, inflation rate, the
amount of money in circulation, the real exchange rate of the
rupiah against the US dollar and interest rates. Indonesia crude
oil price data is the data time series. Time series is said to be
due to the oil price data has the same time interval and
observed in a given period. Besides oil price data have
subjectivity against this oil prices. Subjectivity against oil
price is the value of Linguistics. Therefore, it takes the process
of forecasting time series and linked with the theory of fuzzy.
So this will be developed on the research method of Fuzzy
Time Series Markov Chain Model for predicting the price of
crude oil Indonesia. Fuzzy time series combines the subjective
attitude of the person and the objective historical values can
help solve the problem of forecasting.
In this study, the data used is the daily crude oil price data for
Indonesia from 2010 to 2014. Analysis of forecasting model
which corresponds to the price of crude oil which Indonesia
has always been experiencing fluctuations in the testing done
by the proportion of data, testing the performance of the
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model, as well as comparison testing of forecasting method
with FTS Markov Chain with FTS.
The test results show that the proper forecasting model for
Indonesia crude oil price data is by using Fuzzy Time Series
forecasting method of Markov Chain Model, with the
proportion of 70:30 data, which produces error MAPE SLC of
2.35% 2.53%, Arjuna, Attaka 2.22%, love 2.59% 2.44%,
thorns, Widuri 2.56%, Belida 2.45%, and Senipah Condensate
of 2.36%.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSI 519.535 Wib p |
| Uncontrolled Keywords: | Fuzzy Time Series, Harga Minyak Mentah Indonesia, Peramalan. |
| Subjects: | Q Science > QA Mathematics > QA9.64 Fuzzy logic T Technology > T Technology (General) > T174 Technological forecasting |
| Divisions: | Faculty of Information Technology > Information System > 57201-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Tondo Indra Nyata |
| Date Deposited: | 14 Oct 2019 04:04 |
| Last Modified: | 14 Oct 2019 04:04 |
| URI: | http://repository.its.ac.id/id/eprint/71152 |
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