PERAMALAN HARGA MINYAK MENTAH DUNIA MENGGUNAKAN METODE RADIAL BASIS FUNCTION NEURAL NETWORK - Diponegoro University | Institutional Repository (UNDIP-IR) Rahafatri Arya F

(1)

PERAMALAN HARGA MINYAK MENTAH DUNIA

MENGGUNAKAN METODE

RADIAL BASIS FUNCTION

NEURAL NETWORK

SKRIPSI

Disusun oleh:

Rahafattri Ariya Fauzannissa

24010211140092

JURUSAN STATISTIKA

FAKULTAS SAINS DAN MATEMATIKA

UNIVERSITAS DIPONEGORO

(2)

PERAMALAN HARGA MINYAK MENTAH DUNIA

MENGGUNAKAN METODE

RADIAL BASIS FUNCTION

NEURAL NETWORK

Disusun Oleh :

Rahafattri Ariya Fauzannissa

24010211140092

Skripsi

Sebagai Salah Satu Syarat untuk Memperoleh Gelar

Sarjana Sains pada Jurusan Statistika

JURUSAN STATISTIKA

FAKULTAS SAINS DAN MATEMATIKA

UNIVERSITAS DIPONEGORO

(3)

(4)

(5)

KATA PENGANTAR

Puji dan syukur penulis ucapkan atas kehadirat Allah SWT yang telah

memberikan rahmat dan karunia-Nya sehingga penulis dapat menyelesaikan tugas

akhir dengan judul

Peramalan Harga Minyak Mentah Dunia Menggunakan

Metode

Radial Basis Function Neural Network

_{. Tugas Akhir ini tidak akan}

selesai dengan baik tanpa adanya dukungan dan bantuan dari berbagai pihak.

Ucapan terima kasih penulis haturkan kepada :

1. Ibu Dra. Dwi Ispriyanti, M.Si, sebagai Ketua Jurusan Statistika Fakultas

Sains dan Matematika Universitas Diponegoro dan sekaligus Dosen

Pembimbing II.

2. Bapak Hasbi Yasin, S.Si, M.Si, sebagai Dosen Pembimbing I.

3. Bapak dan Ibu Dosen Jurusan Statistika Fakultas Sains dan Matematika

Universitas Diponegoro

4. Serta semua pihak yang telah membantu kelancaran penyusunan laporan

ini, yang tidak dapat disebutkan satu per satu.

Penulis menyadari bahwa pembuatan Tugas Akhir ini tak luput dari segala

bentuk kesalahan. Oleh karena itu, penulis mengharapkan kritik dan saran yang

membangun untuk perbaikan Tugas Akhir ini. Akhir kata, semoga Tugas Akhir

ini dapat memberikan manfaat bagi semua pihak.

Semarang, November 2015

(6)

v

E

training

sebesar 0,9145 dan nilai MAPE

training

0,74%, sedangkan

untuk MSE

testing

sebesar 4,2739 dan nilai MAPE

testing

adalah 1,63%.

Berdasarkan hasil peramalan, harga minyak mentah dunia pada tanggal 29 Juli

2015 sampai dengan 2 Agustus 2015 berkisar pada angka USD $55,91 per barel.

!"# "!$% &'

:

Radial Basis Function Neural Network (RBFNN), Time Series,

(7)

18

18 ABSTRACT

Oil is the most important commodity in everyday life, because oil is one of

the main source of energy that is needed for the people. Changes in crude oil

prices greatly affect the economic conditions of a country. To forecast crude oil

prices, the past data of the crude oil that is the time series data will be studied so

that will produce crude oil price forecast in the future. Model of Radial Basis

Function Neural Network is suitable for large-scale data processing, because this

model does not require the use of all data input and has a total processing time of

rapid system. This model has a network architecture in the form of input layer,

hidden layer and output layer. Analysis conducted on the data as much as 1286

taken as 100 the data thus obtained value of 0.9145 MSE training and training

MAPE value of 0.74%, while for the testing of 4.2739 MSE and MAPE testing

value is 1.63%. Based on the results of forecasting, crude oil prices on July 29,

2015 until August 2, 2015 at USD $ 55.91 per barrel.

(8)

*+,- +. / 0/

(9)

qrsrtuvw uxy uz wz{|}~ w}| ux rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr

qrr p tuvwuxyuzwz{|}~ w}| ux

qr r p tuvwuxyuzwz{|}~ w }| ux

¡¢ ¢

£r r¤¥p¦¥§ ¨rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr q

£rqr© p ¨¡¥pp¥rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr q

£r£r ¥pp rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr q

£rªr¥ «¬¥ «¡¥ pp¥rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr q

£r rp p¥ pprrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr q

©

§¢¡ § ¢

ªr r¡¥ ¥¥¥®¤ p¥ ¥rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr q£

ªrqr¡¨p¥¯ uw} w} °¦¥¯ zw} °rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr q

ªr£r¡¥ ¥¥ ¢pp±² uvrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr q

ªrªr¡pp«¥ ¦pqsrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr q

ªr r¡¥«p ¥ ¥¤

Euclidean

¥

Training ...

q³

ªr³r¡¥«p ¥ ¥¢pp pop¥

Training ...

q

ªr r¡¥«p ¥ ¥¨¥

Training

rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr qs

ªrsr¡¥«p ¥ ¥¤

Euclidean

¥

Testing...

£

ªrr¡¥«p ¥ ¥¢pp pop¥

Testing...

£q

ªr r¡ ¥ p¥

y

¥ «¥p rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr £ª

©

´§¡µ¢ rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr £³

¶·¡µ§ ´rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr £

(10)

º» ¼½ »¾¿ »À

BA

¾

ÁÂÃ ÂÄ ÂÅ

ÆÂÄÇÂÈÉÊËÌÅÍÎ¸ÏÐÑ¸ÒÂÎ¸ÓÂÔ¸ ÂÃÕÂÎ¸ÎÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ ÉÖ

ÆÂÄÇÂÈÖÊËÌÅÍÎ¸ÏÐÑ¸ÒÂÎ¸×ÅÔÂÐÕ¸ ÅØ È

...

ÉÖ

ÆÂÄÇÂÈÙÊËÌÅÍÎ¸ÏÐÑ¸ÒÂÎ¸Ú¸ Å¸Ø È

...

ÉÙ

ÆÂÄÇÂÈÛÊËÌÅÍÎ¸ÏÐÑ¸ÒÂÎ¸Ü¸ÍÄÝ¸ÔÕ¸ ÅØÈ

...

ÉÛ

ÆÂÄÇÂÈÞÊÏÈÎ¸Ñ ØÐÑ ÌÈ

Radial Basis Function Neural Network ...

Éß

ÆÂÄÇÂÈàÊá¸ÂÍÈÂÄÏÃ¸ÈÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ ÖÖ

ÆÂÄÇÂÈâÊã¸ÄØÜ Ø È¸Ø ÎäÃÝÑÁÂÈÍÂå¸ÅÂÐ

y

åØÅÑÂæáÌÅ¸Â ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ ÖÙ

ÆÂÄÇÂÈçÊäÃÝÑäÏ èËÁÂÈÍÂå¸Å

y

ÂÐåØÅÑÂæáÌÅ¸Â ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ ÖÛ

ÆÂÄÇÂÈßÊäÃÝÑáÂÑÂ

Training

ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ Ùé

ÆÂÄÇÂÈÉéÊäÃÝÑáÂÑÂ

Testing

ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ ÙÛ

(11)

õö÷ öø öù

úöøûüýöùþÿ öö

Training

ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ

úöøûüýöùÿ öö

Testing...

þ

úöøûüýöùÿþ ööý ûü÷ü

...

úöøûüýöùÿöýö

Euclidean

öö

Training

ý ööû öö ý ûü÷ü

...

úöøûüýöùÿù üü ö ü öö

Training

ý ööû öö ý ûü÷ü ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ

úöøûüýöùÿöýö

Euclidean

öö

Testing

ý ööû ööýûü÷ü ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ

úöøûüýöùÿù ü üöü öö

Testing

ý ööû ööýûü÷ü ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿ

(12)

(13)

^_`a_bc de_fghdc_ e_dai j`c da bjda _k _bc lkhf m h_i c b jdejn_nf _d o_ `a_

ij`cda nj`hn_ophn _oq rj g_daf_d o_ `a_ sst g _ k_b dja j`c mc g_f g_u_m gjda _d

bhg_o bjdac f hmc uj`hn_o_d o_ `a_ bcde_f ghdc_v ijoc daa _ ujbj`c dm_o uj`k h

bjk _f hf _d` jwci cmj`o_g_uxysz ijmc_uf_kcmj`{ _ gcf jd_cf _d o_ `a_ bcde_fghdc _

_a _` mjm_u g_u _m bjd ej gc_f _di hni cgc hdmhf `_fe_ mq ^ _k m j`ijn hm gc u_dg_da mc g_f

jljf mc l g_d j lji c jdq t_f _ ujbj `c dm _o uj `kh bj b u`jgc fic o_`a_ bc d e_f ghdc _

ij|_` _mju_mg _d_f h`_mq

}_m _o_ `a_bcd e_fbj`h u_f _di _k_oi_mhg_m_ `hd mhd~ _f mhq}_m _mj`ijn hm

gc uj` kjo u_g_b_i_ k_ kh g_d g_u_mgc ahd_f_d hd mhf b jbu`jgcfi c bjb u`ejfic

g_m_ gc b_i_ bjdg_m_ daq } _k_b ghdc_ i m _mc i mcf _v _g_ gh_ b_| _b b jm gj

ujb gjk _d g _m_v e_c m h bjm gj u_ `_bjm `c f g _d bjm gj d d u _`_b jm `c fq }_k _b

bjm gj u_`_bjm `cf gc f jd_k gh_ _d_kci hdmhf b jdajimc b _i c i h_mh dck_cv e_f dc

(14)

(15)

àóàâñÞóô õ Þ âã ÝÞ ß ãäÝÞ äí âãä èëÝàç ä àéáßà å öãç Þ äÞç ãî ìãäí èàçãñãá ßà çãâãäíÞ

÷àäê çÞ ï Ýãçãè è àç ãâê âãä ÷àäàç ÞñÞãä Ýàä í ãä õê Ýê ç øùú ûüû ýûþ

H

ûú ÿû

ny

û

ù

nt

û þ û ùþ ÿûþ ù

t

ù ûû ý û

s

þ

t

on

ùúû ý ù

tw

ú

.

1.2 Rumusan Masalah

àáÝãï ãáâãäê áãÞã äÝÞãñãïèãâã÷àäê ç Þïèàáêè ê ïâãäèãïãç ãî ìãäíãâ ã ä

ÝÞßãî ãï ãÝãç ãî ßãíãÞèã äã è àäàäñê âãä è ëÝàç ûû ý û

s

þ

t

on

ùúû ý

ù

tw

ú ê äñê â÷àáãèãçã äÝãñ ãî ãáí ãèÞäìã âè àäñãîÝê äÞãå

1.3 Batasan Masalah

ãÝã÷àäàç ÞñÞãäÞäÞÝÞç ãâê âãä÷àèßãñ ãï ãäèãï ãçãîìã Þñê

å æ ãñã ìãäí ÝÞ íê äãâ ãä ãÝ ãç ãî Ýãñ ã îãáíãè Þ äìãâ è àäñãî Ýê äÞã ÷ãÝã ñãîêä

ï ãè÷ãÞÝàäíãäñ ãîêäìãäíÝÞ â àçê ãáâãäëç àîå

å àñëÝà àê áãç àñ é ëáâ ìã äí ÝÞ íê äãâ ãä ãÝãçãî û û ý û

s

þ

t

on

ùú û ý ù

tw

ú å

1.4 Tujuan Penulisan

êõ ê ãä ìãäí Þ äíÞä ÝÞðã÷ãÞ ÝãáÞ ÷àäê çÞ ï ãä Þ äÞ ãÝãç ãî èàäÝã÷ãñ âãä è ëÝàç

û û ý û

s

þ

t

on

ùúû ý ù

tw

ú ê äñ ê â è àáãè ãçâãä î ã áíã èÞä ìãâ