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Lampiran 1. Daftar Istilah

ARIMA Autoregressive Integrate Moving Average

ANN Artificial Neural Network

CART Classification and Regression Tree

CCA Canonical Correlation Analysis

CCC Canadian Climate Center

CSIRO Commonwealth Scientific and Industrial Research Organization

DARLAM Division of Atmospheric Research Limited Area Model

DPM Daerah Prakiraan Musim

DPM_BMG DPM hasil pewilayahan olen BMG (2003) DPM_PPR DPM hasil pewilayahan dengan model PPR GCM General Circulation Model

GFDL Geophysical Fluid Dynamic Laboratory

GISS Goddard Institute for Space Studies

LAM Limited Area Model

MARS Multivariate Additive Regression Spline

MOS Model Output Statistics

NCAR National Centre for Atmospheric Research

NCEP National Centers for Environmental Prediction

NHMM Non Homogenuous Hidden Markov Model

NWP Numerical Weather Prediction

NWS National Weather Services

PCA Principal Component Analysis

PCR Principal Component Regression

PP Projection Pursuit

PPR Projection Pursuit Regression

RCM Regional Circulation Model

RMSEP Root Mean Square Error of Prediction

TSR Tree Structure Regression

UKMO United Kingdom Meteorological Office

UKTR United Kingdom Meteorological Transient

SD Statistical Downscaling

SLP Sea Level Pressure

SST Sea Surface Temperature

STD Standard Deviation

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Lampiran 2.

Elevasi dan Koordinat Setiap Stasiun di Kabupaten Indramayu

No Stasiun Nama Stasiun Elevasi(mdpl) LS BT

1a Bugel 1 6,299 107,985 10 Indramayu 6 6,345 108,322 10a Cidempet 7 6,352 108,247 1 Anjatan 1 6,355 107,954 1c Tulangkacang 1 6,357 107,006 4 Bulak/Kandanghaur 2 6,363 108,113 11 Bangkir 11 6,385 108,291 2a Bugis 7 6,389 107,932 17 Karangasem 24 6,395 107,054 23a Sudimampir 4 6,402 108,366 7 Losarang 2 6,405 108,149 12 Lohbener 11 6,406 108,282 16 Wanguk 1 6,416 107,957 15 Luwungsemut 8 6,427 107,009 9a Tugu * 6,433 108,333 23b Juntinyuat 5 6,433 108,438 5 Gabuswetan 8 6,445 107,039 13b Jatibarang 3 6,456 108,307 23 Ujungaris 12 6,457 108,287 8 Cikedung * 6,467 108,167 13a Sudikampiran 7 6,482 108,364 29 Temiyang 26 6,487 107,021 18b Cipancuh 8 6,488 107,944 6 Kroya 48 6,489 107,064 26 Krangkeng 5 6,503 108,483 27 Kedokan Bunder 7 6,509 108,424 9 Sumurwatu * 6,517 108,1 3b Gantar 22 6,528 107,973 14 Sukadana 18 6,546 108,315 3c Bantarhuni 35 6,589 107,951 14b Bondan 9 6,606 108,299

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Lampiran 3

. Dendrogram Pengelompokan Stasiun Curah Hujan Sukra Indr amay Buge l Wan guk Cid e mpe t Ujga ris Bula k Lohb ener Losa rang Bang kir Sudi mam p Kedk nbun Kran gken Junti nyu Sudi kam p Jatib ara T lka cang Lwse mu t Kroy a Krga sem Gbsw etan Bugi s Anj a tan Tug u Cike dung Suka dana Tem i yang Gant ar Bant arhu Bond an Cipa ncuh Sum urwa t 31.50 54.33 77.17 100.00 Similarity Stasiun

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Lampiran 4

. Curah Hujan (mm) Aktual dan Dugaan Setiap DPM_PPR

DPM1_PPR 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan DPM2_PPR 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan DPM3_PPR 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan DPM4_PPR 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan DPM5_PPR 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan

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Lampiran 5

. Curah Hujan (mm) Aktual dan Dugaan Setiap DPM_BMG DPM1_BMG 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan DPM2_BMG 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan DPM3_BMG 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan DPM4_BMG 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan DPM5_BMG 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan DPM6_BMG 0 100 200 300 400 500 1 2 3 4 5 6 7 8 9 10 11 12 Aktual Dugaan

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Lampiran 6

. Sub-Program S-Plus yang digunakan untuk Pendugaan Model PPR

ppreg(x, y, min.term, max.term=min.term, wt=rep(1,nrow(x)), rwt=rep(1,ncol(y)), xpred=NULL,optlevel=2,bass=0,span="cv") Outputs by ppreg:

ypred

matrix of predicted values for y given the matrix xpred. If xpred was not input, then ypred contains the residuals for the model fit.

fl2

the sum of squared residuals divided by the total corrected sums of squares.

alpha

a minterm by ncol(x) matrix of the direction vectors, alpha[m,j] contains the j-th component of the direction in the m-th term.

beta

a minterm by ncol(y) matrix of term weights, beta[m,k] contains the value of the term weight for the m-th term and the k-th response variable.

z

a matrix of values to be plotted against zhat. z[i,m] contains the z value of the i-th observation in the m-th model term, i.e., z equals x %*% t(alpha). The columns of z have been sorted.

zhat

a matrix of function values to be plotted. zhat[i,m] is the smoothed ordinate value (phi) of the i-th observation in the m-th model term evaluated at z[i,m].

allalpha

a three dimensional array, the [m,j,M] element contains the j -th component of the direction in the m-th model term for the solution consisting of M terms. Values are zero for M less than minterm.

allbeta

a three dimensional array, the [m,k,M] element contains the term weight for the m-th term and the k-th response variable for the solution consisting of M terms. Values are zero for M less than minterm.

esq

esq[M] contains the fraction of unexplained variance for the solution consisting of M terms. Values are zero for M less than minterm.

esqrsp

matrix that is ncol(y) by maxterm containing the fraction of

unexplained variance for each response. esqrsp[k,M] is for the k-th response variable for the solution consisting of M terms, for M ranging from min.term to max.term. Other columns are zero.