492 XXXXXXXXXXXXX
492 XXXXXXXXXXXXX - LAMPIRAN-LAMPIRAN - PERAMALAN RUNTUN WAKTU MENGGUNAKAN MODEL FUNGSI TRANSFER MULTIVARIAT
===
0 0.492 XXXXXXXXXXXXX
1 -0.226
XXXXXXX
XXXXXXXXXX
3 -0.112
XXXX
5 -0.154
XXXXX
XX
XX
7 -0.038
XX
XX
%============================================================================= %Hasil estimasi Parameter Model ARIMA Kecepatan Angin yang Telah Diputihkan
CCF - correlates alfa3(t) and beta3(t+k)
-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0
+----+----+----+----+----+----+----+----+----+----+
XX
-17 -0.036
XX
-16 -0.038
-15 -0.218
XXXXXX
-14 0.075
XXX
XX
-13 -0.036
-12 0.148
XXXXX
XX
-11 -0.051
-10 0.197
XXXXXX
-9 -0.065
XXX
-8 -0.067
XXX
-7 0.090
XXX
%============================================================================= %Hasil estimasi Parameter Model ARIMA Suhu Udara yang Telah Diputihkan
CCF - correlates alfa4(t) and beta4(t+k)
-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 +----+----+----+----+----+----+----+----+----+----+ -17
0.080
XXX
-16 0.165
XXXXX
-15 -0.092
XXX
-14 -0.011
-13 -0.013
-12 -0.005
-11 -0.089
XXX
-10 0.190
XXXXXX
-9 -0.113
XXXX
-8 0.124
XXXX
-7 -0.109
XXXX
-6 -0.078
XXX
XX
-5 0.053
-4 -0.095
XXX
-3 0.138
XXXX
-2 -0.246
XXXXXXX
-1 0.378
XXXXXXXXXX
0 -0.388
XXXXXXXXXXX
1 0.254
XXXXXXX
2 -0.266
XXXXXXXX
XX
3 -0.026
%============================================================================= %Hasil estimasi Parameter Model ARIMA Intensitas Matahari yang Telah Diputihkan
CCF - correlates alfa5(t) and beta5(t+k)
-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 +----+----+----+----+----+----+----+----+----+----+ -17
XXX
-16 -0.004
-15 -0.145
XXXXX
XX
-13 -0.289
XXXXXXXX
-12 -0.006
XXXXX
XX
-10 -0.044
XXXXXXXXX
XXXX
-7 -0.111
XXXX
XXXXXX
XX
-5 -0.025
-4 -0.177
XXXXX
XXX
-2 -0.119
XXXX
-1 -0.134
XXXX
XX
0 -0.046
1 -0.293
XXXXXXXX
XX
XX
4 -0.193
XXXXXX
XXX
XX
8 -0.207
XXXXXX
XXXXX
XXX
11 -0.019
12 -0.019
13 -0.064
XXX
XXXXXXX
XXXX
XXXXX
LAMPIRAN 8
Estimasi Penentuan (r, s, b) Berdasarkan Crosscorrelation %Korelasi Silang Tekanan Udara
Crosscorrelations
Lag Covariance
Correlation
-1 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 1
-17 0.075253
. | -16
0.01216
. | -15
-0.814516
-.13158
. ***|
|*** . | -14
0.986301
0.15934
. | -13
0.637142
0.10293
|**
. | -12
-0.138651
-.02240
. | -11
0.222067
0.03587
|*
|*****. | -10
1.666078
0.26915
. | -9
0.050725
0.00819
. | -8
-0.906409
-.14643
. ***|
. | -7
-0.813909
-.13149
. ***|
. | -6
-0.642594
-.10381
**|
. | -5
0.019182
0.00310
. | -4
-1.245417
-.20120
. ****|
. | -3
-1.403061
-.22666
.*****|
. | -2
-0.141475
-.02286
. | -1
-0.814260
-.13154
. ***|
-3.175849
-.51306
**********|
. | %--------------------------------------------------------------------------- %Korelasi Silang Kelembaban Udara Crosscorrelations
Lag Covariance
Correlation
. | -16
|*****. | -14
. | -13
|*** . | -12
. | -11
|*****. | -10
. | -9
. | -8
. | -7
. | -6
. | -5
. | -4
. | -3
. | -2
|**** . | -1
1 -3.798592
3 -1.843036
5 -2.550708
7 -0.535250
9 -0.212387
10 -4.150407
. | %--------------------------------------------------------------------------- %Korelasi Silang Kecepatan Angin Crosscorrelations
Lag Covariance
Correlation
-1 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 1
-17 -0.198259
. | -16
-.05408
*|
. | -15
-0.174567
-.04762
*|
. | -14
-0.762399
-.20797
. ****|
. | -13
0.416872
0.11371
|**
. | -12
-0.122682
-.03347
*|
|*** . | -11
0.568788
0.15515
. | -10
-0.316092
-.08622
**|
|*** . | -9
0.539950
0.14729
. | -8
-0.061228
-.01670
. | -7
-0.399384
-.10894
**|
. | -6
0.282755
0.07713
|**
. | -5
0.297526
0.08116
|**
0.358542
0.09780
|**
|****** | %--------------------------------------------------------------------------- %Korelasi Silang Suhu Udara Crosscorrelations
Lag Covariance
Correlation
-1 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 1
-17 0.048760
. | -16
0.02368
|**** . | -15
0.420547
0.20423
. | -14
-0.258837
-.12570
. ***|
. | -13
0.178852
0.08686
|**
. | -12
-0.184476
-.08959
**|
. | -11
0.0026211
0.00127
. | -10
-0.153701
-.07464
*|
|*** . | -9
0.262756
0.12760
. | -8
-0.080372
-.03903
*|
. | -7
0.192778
0.09362
|**
. | -6
-0.253298
-.12301
**|
. | -5
-0.030653
-.01489
. | -4
0.038340
0.01862
. | -3
-0.194569
-.09449
**|
|**** . | -2
0.436816
0.21213
. | -1
-0.165070
-.08016
**|
0.417088
0.20255
|**** . |
0 -0.911569
-.44269
*********|
1 0.355800
0.17279
|*** . |
2 -0.359821
-.17474
. ***|
3 -0.015039
-.00730
4 0.115027
0.05586
|*
5 0.050846
0.02469
6 0.350387
0.17016
|*** . |
. | %--------------------------------------------------------------------------- %Korelasi Silang Intensitas Matahari Crosscorrelations
Lag Covariance
Correlation
. | -16
. | -15
. | -14
. | -13
. | -12
. | -11
. | -10
. | -9
. | -7
. | -6
|*****. | -5
. | -4
. | -3
. | -2
. | -1
0 -3.413035
1 -11.379797
4 -9.214993
8 -8.461837
11 -0.089996
12 -0.450921
13 -3.449248
16 -1.423058
LAMPIRAN 9 Output SAS hasil Estimasi Parameter
%Hasil estimasi Parameter Model ARIMA untuk Tekanan Udara
The ARIMA Procedure Conditional Least Squares Estimation
Approx Parameter
t Value
Pr> |t| Lag
2 AR1,1
MA1,1 -0.34190
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr>
Lag Square DF ChiSq ------------Autocorrelations------------
12 12.61 10 0.2462 -0.256 -0.093 -0.089 -0.105 -0.067 -0.134
24 28.64 22 0.1554 -0.049 -0.020 -0.163 -0.084 -0.118 -0.295 %------------------------------------------------------------------- %Hasil estimasi Parameter Model ARIMA untuk Kelembaban Udara
The ARIMA Procedure
Conditional Least Squares Estimation
Approx Parameter
t Value
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr>
Lag Square DF ChiSq ------------Autocorrelations------------
0.194 -0.175 -0.035
0.068 -0.146 -0.016 -0.016 0.006 -0.444
0.118 -0.099
0.081 -0.104 0.061 -0.043
0.038 -0.062 -0.022 -0.017 0.073 %---------------------------------------------------------------------- %Hasil estimasi Parameter Model ARIMA untuk Kecepatan Angin
The ARIMA Procedure
Conditional Least Squares Estimation
Standard
Approx
Parameter Estimate
Error
t Value
Pr> |t| Lag
MA1,1 -0.39049
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr>
Lag Square DF ChiSq ------------Autocorrelations------------
0.074 -0.189 -0.030 0.054 -0.174
0.110 -0.052 -0.136 %------------------------------------------------------------------------ %Hasil estimasi Parameter Model ARIMA untuk Suhu Udara
The ARIMA Procedure
Conditional Least Squares Estimation
Standard
Approx
Parameter Estimate
Error
t Value
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr>
Lag Square DF ChiSq ------------Autocorrelations------------
0.099 -0.013 -0.007
0.153 -0.045 0.066 -0.040
0.120 0.131 0.104 %------------------------------------------------------------------------- %Hasil estimasi Parameter Model ARIMA untuk Intensitas Matahari
The ARIMA Procedure
Conditional Least Squares Estimation
Standard
Approx
Parameter Estimate
Error
t Value
Pr> |t|
Lag
MA1,1 0.73968
12 AR1,1
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr>
Lag Square DF ChiSq ------------Autocorrelations------------
-0.013 -0.010
0.246 -0.239 -0.059 -0.077
0.102 -0.120 0.035 -0.006
0.065 -0.180 0.011 -0.031 %------------------------------------------------------------------------ %Hasil estimasi Parameter Model Fungsi Transfer untuk Tekanan Udara
The ARIMA Procedure
Conditional Least Squares Estimation
Standard
Approx
Parameter Estimate
Error
t Value
Pr > |t| Lag
Variable Shift
AR1,1 -0.63305
12 Ysqrt NUM1
0 X1 2 NUM1,1
2 X1 2 DEN1,1
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr >
Lag Square DF ChiSq ------------Autocorrelations------------
Crosscorrelation Check of Residuals with Input X1
To Chi-
Pr >
Lag Square
DF ChiSq
0.156 -0.125 %------------------------------------------------------------------------ %Hasil estimasi Parameter Model Fungsi Transfer untuk Kelembaban Udara
The ARIMA Procedure
Conditional Least Squares Estimation
Standard
Approx
Parameter Estimate
Error
t Value
Pr > |t|
Lag
Variable Shift
MA1,1 0.59054
12 Ysqrt NUM1
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr >
Lag Square
DF ChiSq
Crosscorrelation Check of Residuals with Input X2
To Chi-
Pr >
Lag Square
DF ChiSq
0.141 0.183 %------------------------------------------------------------------------ %Hasil estimasi Parameter Model Fungsi Transfer untuk Kecepatan Angin
The ARIMA Procedure Conditional Least Squares Estimation
Standard
Approx
Parameter Estimate
Error
t Value
Pr > |t|
Lag
Variable Shift
AR1,1 -0.61286
12 Ysqrt NUM1
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr >
Lag Square
DF ChiSq
Crosscorrelation Check of Residuals with Input X3
To Chi-
Pr >
Lag Square
DF ChiSq
0.136 0.084 %------------------------------------------------------------------------ %Hasil estimasi Parameter Model Fungsi Transfer untuk Suhu Udara
The ARIMA Procedure Conditional Least Squares Estimation
Standard
Approx
Parameter Estimate
Error
t Value
Pr > |t|
Lag
Variable Shif
AR1,1 -0.44274
12 Ysqrt NUM1
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr >
Lag Square
DF ChiSq
Crosscorrelation Check of Residuals with Input X4
To Chi-
Pr >
Lag Square
DF ChiSq
-0.064 -0.083 %------------------------------------------------------------------------ %Hasil estimasi Parameter Model Fungsi Transfer untuk Intensitas Matahari
The ARIMA Procedure Conditional Least Squares Estimation
Standard
Approx
Parameter Estimate
Error
t Value
Pr > |t|
Lag
Variable Shift
AR1,1 -0.48352
12 Ysqrt NUM1
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr >
Lag Square
DF ChiSq
Crosscorrelation Check of Residuals with Input X5
To Chi-
Pr >
Lag Square
DF ChiSq
------------Crosscorrelations------------
-0.199 0.016 %------------------------------------------------------------------------ %Hasil estimasi Parameter Model Fungsi Transfer Multivariat
The ARIMA Procedure Conditional Least Squares Estimation
Standard
Approx
Parameter Estimate
Error
t Value
Pr > |t|
Lag
Variable Shift
AR1,1 -0.91530
12 Ysqrt NUM1
0 X1 2 NUM1,1
2 X1 2 DEN1,1
6 X1 2 NUM2
0 X2 0 NUM3
Variance Estimate
Std Error Estimate
Number of Residuals
* AIC and SBC do not include log determinant.
Autocorrelation Check of Residuals
To Chi-
Pr >
Lag Square
DF ChiSq
Crosscorrelation Check of Residuals with Input X1
To Chi-
Pr >
Lag Square
DF ChiSq
------------Crosscorrelations------------
5 5.69 3 0.1278 -0.138 -0.078 -0.144 -0.012
0.055 -0.105 -0.057 -0.129 -0.065
23 23.03 21 0.3424 -0.207 -0.046 -0.083
0.020 -0.015 -0.042
Crosscorrelation Check of Residuals with Input X2
To Chi-
Pr >
Lag Square
DF ChiSq
0.069 -0.069 -0.044 -0.404
17 16.39 17 0.4966 -0.064 -0.058 -0.122 -0.201 -0.119 -0.077
29 22.01 29 0.8196 -0.001 -0.024
0.044 -0.031 -0.013 -0.037
0.019 -0.009
Crosscorrelation Check of Residuals with Input X3
To Chi-
Pr >
Lag Square
DF ChiSq
------------Crosscorrelations------------
5 7.53 5 0.1841 -0.012 -0.069 -0.228 -0.086 -0.135 -0.326
0.121 -0.067 -0.061
0.010 -0.147 -0.011 -0.025 0.056
0.003 -0.012 -0.030 -0.000 %------------------------------------------------------------------------ %Hasil Ramalan Curah Hujan tahun 2013-2014 Obs
35 19.20 35 0.9861 -0.028 -0.016
Forecast
Std Error
95% Confidence Limits
Actual Residual
LAMPIRAN 10 Tabel Chi-Square