Syarifah, Uzlifatus (2015) Analisis Peramalan Penjualan Premium dan Solar di PT. Pertamina (Persero) Regional V Surabaya Menggunakan Metode ARIMAX dan Regresi Time Series. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Peningkatan volume kendaraan yang diproduksi menyatakan
semakin banyak tingkat kebutuhan bahan bakar minyak untuk pengguna
kendaraan bermotor setiap hari, khususnya wilayah Surabaya yang
mendominasi kendaraan roda dua maupun roda empat. Dispenda
(2015) menyatakan bahwa jumlah kendaraan naik sebanyak 200.000
kendaraan tiap tahunnya. Seiring banyaknya aktivitas yang dilakukan
manusia setiap hari membuat kebutuhan bahan bakar semakin
meningkat, terutama bagi masyarakat perkotaan sebagai contoh kota
Surabaya yang memiliki tingkat mobilitas tinggi dimana seringkali
terjadi keterlambatan pendistribusian yang mengakibatkan kelangkaan
premium dan solar yang penjualannya tinggi dan sifatnya fluktuatif,
maka permasalahannya adalah bagaimana menentukan dan
mendapatkan model yang sesuai untuk meramalkan volume penjualan
premium dan solar pada tahun 2015 menggunakan metode ARIMA,
ARIMAX, dan Regresi Time Series dengan melihat karakteristik
penjualan premium dan solar tahun 2008-2014 pada tampilan
Dashboard. Variabel yang digunakan yaitu volume penjualan premium
dan solar. Berdasarkan kriteria model terbaik diperoleh kesimpulan
bahwa metode yang sesuai adalah model ARIMA (0,1,1) (0,1,0)12 untuk
meramalkan penjualan premium. Sedangkan untuk meramalkan solar
metode yang sesuai adalah model Regresi Time Series.
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An increase in the volume of vehicles produced stating the more the
level of fuel needs for users of motor vehicles every day, especially
Surabaya area that dominates the two-wheeler and four wheels.
Dispenda (2015) stated that the number of vehicles rose 200,000
vehicles each year. As the number of activities that humans do every day
makes the need for fuel is increasing, especially for urban communities
as an example the city of Surabaya, which has a high level of mobility
where often there is a delay distribution resulting in scarcity of gasoline
and diesel were high and its sales fluctuate, then the problem is how
determine and obtain the appropriate model to forecast sales volume of
gasoline and diesel by 2015 using ARIMA, ARIMAX, and Regression
Time Series by looking at the characteristics of gasoline and diesel fuel
sales 2008-2014 in the Dashboard display. Variables used are the sales
volume of gasoline and diesel. Based on the criteria for best model we
concluded that the appropriate method is ARIMA (0,1,1) (0,1,0)12
premium to forecast sales. As for predicting solar suitable method is
Regression models Time Series.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSt 519.536 Sya a |
| Uncontrolled Keywords: | ARIMA, ARIMAX, BBM, dan Regresi Time Series |
| Subjects: | Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression |
| Divisions: | Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Yeni Anita Gonti |
| Date Deposited: | 24 Feb 2020 03:47 |
| Last Modified: | 24 Feb 2020 03:47 |
| URI: | http://repository.its.ac.id/id/eprint/75130 |
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