Saran Penelitian Lanjutan KESIMPULAN DAN IMPLIKASI KEBIJAKAN
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LAMPIRAN
Lampiran 1. Program Komputer Estimasi Model Ekonomi Rumahtangga Petani Menggunakan SASETS Prosedur SYSLIN Metode 2 SLS.
options nodate nonumber; DATA BERAS;
INPUT; cards;
; data stress;
merge beras; by no; create data
NPU = JPUHREA; NTSP = JPTHTSP;
NPL= JPLHPL; NPB= JPBHB;
UPJ = UP6; NTKDK = TKDKUPJ;
NTKLK = TKLKUPJ; NTKER = NTKDK + NTKLK;
BUT = NPU + NTSP + NPL + NPB + NTKER + BL; PDP = PRDI HPDI;
PUTP = PDP - BUT; PTP = PUTP + PUTNP;
PTRT = PTP + PBNP + PBP + PL; PI = PPK + PKS;
TPRT = NPPG + PNP + PI; run;
proc syslin 2sls data=stress outest=hasil2; endogenous GRPN PRDI JPU JPT JPB HPL TKDK TKLK TKER TKNP
BUT PDJ PTJ PTP PUTP PUTNP PBNP PTRT PL PDI PI NPPG PNP KSP RPP PPK PKS TAB AKE TPRT;
instruments HPDI HREA PUAP JAKE HTSP UP NPU NTSP NPDJ PDP NTKER NPL NPB BL PKK UNP PAJK
JAK HBR NPPT PGR CST JAS JP KE; persamaan struktural
LUAS_GRP: MODEL GRPN= HPDI PUAP TAB NPPG DW; PROD_PDI: MODEL PRDI= JPU JPB GRPN TKER DW;
JML_UREA: MODEL JPU = HREA TKDK GRPN DW; JMLH_TSP: MODEL JPT = HTSP TKLK GRPN PUAP DW;
JAM_TKDK: MODEL TKDK= JAKE TKLK GRPN DW; JAM_TKLK: MODEL TKLK= UP TKDK GRPN DW;
JAM_TKNP: MODEL TKNP= PBNP TKLK PI DW; PDPT_BRH: MODEL PBNP = TKNP JAKE UNP DW;
NLAI_PPG: MODEL NPPG= PRDI JAS NPPT PGR DW; PENG_PDK: MODEL PPK = PTRT NPPG JAS DW;
PENG_PKS: MODEL PKS = PTRT AKE PPK DW; PENG_NPG: MODEL PNP = PTRT JAS PUAP DW;
ANGK_KEN: MODEL AKE = PTRT NPPG JAK DW; NLAI_TAB: MODEL TAB = PTRT CST PKS PUAP DW;
persamaan identitas
IDENTITY TKER = TKDK + TKLK; IDENTITY BUT = NPU + NTSP + NPL + NPB + NTKER + BL;
IDENTITY PUTP = PDP - BUT; IDENTITY PTP = PUTP + PUTNP;
IDENTITY PTRT = PTP + PBNP + PBP + PL; IDENTITY PI = PPK + PKS;
IDENTITY TPRT = NPPG + PNP + PI; run;
Lampiran 2. Hasil Estimasi Model Ekonomi Rumahtangga Petani Menggunakan SASETS Prosedur SYSLIN Metode 2 SLS
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model LUAS_GRP
Dependent Variable GRPN Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 3 0.023757 0.007919 2.53 0.0727 Error 36 0.112791 0.003133
Corrected Total 39 0.135469 Root MSE 0.05597 R-Square 0.17398
Dependent Mean 0.20963 Adj R-Sq 0.10515 Coeff Var 26.70198
WARNING: The model is not of full rank. Least Squares solutions for the parameters are not unique.
Certain statistics will be misleading. A reported degree of freedom of 0 or B means the
estimate is biased. The following parameters have been set to zero. These variables are a linear
combination of other variables as shown.
Intercept = +0.000250 HPDI Parameter Estimates
Parameter Standard Variable DF Estimate Error t Value Pr |t|
Intercept 0 0 . . . HPDI 0 0.000046 8.312E-6 5.58 .0001
PUAP 1 3.172E-8 1.411E-8 2.25 0.0307 TAB 1 9.4E-10 2.156E-9 0.44 0.6654
NPPG 1 -6.89E-9 8.409E-9 -0.82 0.4182 Durbin-Watson 1.936269
Number of Observations 40 First-Order Autocorrelation -0.06869
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model PROD_PDI
Dependent Variable PRDI Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 4 2433633 608408.3 7.48 0.0002
Error 35 2846138 81318.22 Corrected Total 39 5088710
Root MSE 285.16351 R-Square 0.46094 Dependent Mean 488.50000 Adj R-Sq 0.39933
Coeff Var 58.37533 Parameter Estimates
Parameter Standard Variable DF Estimate Error t Value Pr |t|
Intercept 1 -14.8353 217.9093 -0.07 0.9461 JPU 1 2.190359 1.225647 1.79 0.0826
JPB 1 13.57680 5.126352 2.65 0.0120 GRPN 1 497.4720 1413.485 0.35 0.7270
TKER 1 0.061583 0.271683 0.23 0.8220 Durbin-Watson 2.222394
Number of Observations 40 First-Order Autocorrelation -0.11218
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model JML_UREA
Dependent Variable JPU Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 2 46393.37 23196.68 11.67 0.0001 Error 37 73564.51 1988.230
Corrected Total 39 104509.4 Root MSE 44.58957 R-Square 0.38675
Dependent Mean 84.37500 Adj R-Sq 0.35360 Coeff Var 52.84690
WARNING: The model is not of full rank. Least Squares solutions for the parameters are not unique.
Certain statistics will be misleading. A reported degree of freedom of 0 or B means the
estimate is biased. The following parameters have been set to zero. These variables are a linear
combination of other variables as shown.
Intercept = +0.000556 HREA Parameter Estimates
Parameter Standard Variable DF Estimate Error t Value Pr |t|
Intercept 0 0 . . . HREA 0 -0.03383 0.017206 -1.97 0.0568
TKDK 1 0.108447 0.219370 0.49 0.6240 GRPN 1 681.7279 141.6328 4.81 .0001
Durbin-Watson 1.782083 Number of Observations 40
First-Order Autocorrelation 0.104918
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model JMLH_TSP
Dependent Variable JPT Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 3 9687.597 3229.199 4.06 0.0139 Error 36 28627.34 795.2040
Corrected Total 39 35499.40 Root MSE 28.19936 R-Square 0.25284
Dependent Mean 35.62850 Adj R-Sq 0.19058 Coeff Var 79.14833
WARNING: The model is not of full rank. Least Squares solutions for the parameters are not unique.
Certain statistics will be misleading. A reported degree of freedom of 0 or B means the
estimate is biased. The following parameters have been set to zero. These variables are a linear
combination of other variables as shown.
Intercept = +0.000714 HTSP Parameter Estimates
Parameter Standard Variable DF Estimate Error t Value Pr|t|
Intercept 0 0 . . . HTSP 0 -0.02111 0.014202 -1.49 0.1459
TKLK 1 -0.01618 0.026371 -0.61 0.5433 GRPN 1 281.3177 109.8032 2.56 0.0147
PUAP 1 6.749E-6 7.622E-6 0.89 0.3818 Durbin-Watson 2.534868
Number of Observations 40 First-Order Autocorrelation -0.26754
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model JAM_TKDK
Dependent Variable TKDK Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 3 4104.006 1368.002 0.85 0.4737 Error 36 57660.57 1601.683
Corrected Total 39 62580.40 Root MSE 40.02103 R-Square 0.06645
Dependent Mean 21.80000 Adj R-Sq -0.01135 Coeff Var 183.58269
Parameter Estimates Parameter Standard
Variable DF Estimate Error t Value Pr|t| Intercept 1 -0.16701 31.60344 -0.01 0.9958
JAKE 1 11.09120 7.074881 1.57 0.1257 TKLK 1 -0.02247 0.038046 -0.59 0.5584
GRPN 1 23.07147 140.6626 0.16 0.8706 Durbin-Watson 2.208143
Number of Observations 40 First-Order Autocorrelation -0.10945
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model JAM_TKLK
Dependent Variable TKLK Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 3 255391.9 85130.62 2.30 0.0937 Error 36 1332041 37001.14
Corrected Total 39 1534526 Root MSE 192.35680 R-Square 0.16088
Dependent Mean 150.75000 Adj R-Sq 0.09096 Coeff Var 127.59987
Parameter Estimates Parameter Standard
Variable DF Estimate Error t Value Pr|t| Intercept 1 -171.476 134.1796 -1.28 0.2094
UP 1 -0.00026 0.001275 -0.21 0.8379 TKDK 1 -0.34272 0.952001 -0.36 0.7210
GRPN 1 1602.413 618.4120 2.59 0.0137 Durbin-Watson 1.942982
Number of Observations 40 First-Order Autocorrelation 0.028452
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model JAM_TKNP
Dependent Variable TKNP Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 3 5698957 1899652 127.17 .0001 Error 36 537771.9 14938.11
Corrected Total 39 7129120 Root MSE 122.22156 R-Square 0.91377
Dependent Mean 177.90000 Adj R-Sq 0.90659 Coeff Var 68.70239
Parameter Estimates Parameter Standard
Variable DF Estimate Error t Value Pr|t| Intercept 1 -33.3652 44.14112 -0.76 0.4546
PBNP 1 0.000173 9.15E-6 18.88 .0001 TKLK 1 0.027848 0.106110 0.26 0.7945
PI 1 0.000013 0.000020 0.65 0.5229 Durbin-Watson 2.364161
Number of Observations 40 First-Order Autocorrelation -0.18254
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model PDPT_BRH
Dependent Variable PBNP Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 3 1.894E14 6.312E13 532.83 .0001 Error 36 4.265E12 1.185E11
Corrected Total 39 2.094E14 Root MSE 344196.132 R-Square 0.97797
Dependent Mean 1068000.00 Adj R-Sq 0.97614 Coeff Var 32.22810
Parameter Estimates Parameter Standard
Variable DF Estimate Error t Value Pr|t| Intercept 1 -623334 136586.5 -4.56 .0001
TKNP 1 4288.299 196.2302 21.85 .0001 JAKE 1 69517.66 61048.24 1.14 0.2623
UNP 1 49.98989 5.895421 8.48 .0001 Durbin-Watson 2.895002
Number of Observations 40 First-Order Autocorrelation -0.44816
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model NLAI_PPG
Dependent Variable NPPG Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 4 4.185E13 1.046E13 52.23 .0001 Error 35 7.012E12 2.003E11
Corrected Total 39 4.887E13 Root MSE 447596.746 R-Square 0.85650
Dependent Mean 2947850.00 Adj R-Sq 0.84010 Coeff Var 15.18384
Parameter Estimates Parameter Standard
Variable DF Estimate Error t Value Pr|t| Intercept 1 923868.0 474052.5 1.95 0.0594
PRDI 1 -876.241 208.9698 -4.19 0.0002 JAS 1 -11022.4 127512.0 -0.09 0.9316
NPPT 1 1.117334 0.078421 14.25 .0001 PGR 1 -434.068 6069.960 -0.07 0.9434
Durbin-Watson 1.549651 Number of Observations 40
First-Order Autocorrelation 0.177833
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model PENG_PDK
Dependent Variable PPK Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 3 1.216E13 4.055E12 3.18 0.0356 Error 36 4.595E13 1.276E12
Corrected Total 39 5.877E13 Root MSE 1129777.63 R-Square 0.20932
Dependent Mean 1646549.70 Adj R-Sq 0.14343 Coeff Var 68.61485
Parameter Estimates Parameter Standard
Variable DF Estimate Error t Value Pr|t| Intercept 1 903596.8 727589.5 1.24 0.2223
PTRT 1 0.012384 0.034036 0.36 0.7181 NPPG 1 -0.17954 0.168821 -1.06 0.2946
JAS 1 848719.9 315451.2 2.69 0.0107 Durbin-Watson 1.756852
Number of Observations 40 First-Order Autocorrelation 0.110517
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model PENG_PKS
Dependent Variable PKS Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 3 8.745E10 2.915E10 0.91 0.4481 Error 36 1.159E12 3.22E10
Corrected Total 39 1.202E12 Root MSE 179447.629 R-Square 0.07015
Dependent Mean 61525.0000 Adj R-Sq -0.00734 Coeff Var 291.66620
Parameter Estimates Parameter Standard
Variable DF Estimate Error t Value Pr|t| Intercept 1 309606.8 155784.1 1.99 0.0545
PTRT 1 0.002387 0.005709 0.42 0.6784 AKE 1 -4037.75 2540.537 -1.59 0.1207
PPK 1 -0.02008 0.030628 -0.66 0.5162 Durbin-Watson 2.29745
Number of Observations 40 First-Order Autocorrelation -0.15892
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model PENG_NPG
Dependent Variable PNP Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 3 3.006E14 1.002E14 3.71 0.0200 Error 36 9.71E14 2.697E13
Corrected Total 39 1.228E15 Root MSE 5193494.30 R-Square 0.23637
Dependent Mean 7529475.00 Adj R-Sq 0.17274 Coeff Var 68.97552
Parameter Estimates Parameter Standard
Variable DF Estimate Error t Value Pr|t| Intercept 1 2784103 2733611 1.02 0.3153
PTRT 1 0.177213 0.166803 1.06 0.2951 JAS 1 -818395 1460254 -0.56 0.5786
PUAP 1 3.406815 1.330138 2.56 0.0148 Durbin-Watson 1.704526
Number of Observations 40 First-Order Autocorrelation 0.079849
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model ANGK_KEN
Dependent Variable AKE Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 3 2933.347 977.7825 12.10 .0001 Error 36 2907.944 80.77622
Corrected Total 39 5674.083 Root MSE 8.98756 R-Square 0.50217
Dependent Mean 58.27371 Adj R-Sq 0.46069 Coeff Var 15.42301
Parameter Estimates Parameter Standard
Variable DF Estimate Error t Value Pr|t| Intercept 1 73.24976 6.567416 11.15 .0001
PTRT 1 6.39E-7 2.656E-7 2.41 0.0214 NPPG 1 1.991E-6 1.355E-6 1.47 0.1503
JAK 1 -6.61001 1.224703 -5.40 .0001 Durbin-Watson 1.598133
Number of Observations 40 First-Order Autocorrelation 0.032627
The SAS System The SYSLIN Procedure
Two-Stage Least Squares Estimation Model NLAI_TAB
Dependent Variable TAB Analysis of Variance
Sum of Mean Source DF Squares Square F Value PrF
Model 4 4.457E14 1.114E14 5.10 0.0024 Error 35 7.652E14 2.186E13
Corrected Total 39 1.086E15 Root MSE 4675745.76 R-Square 0.36807
Dependent Mean 3909625.00 Adj R-Sq 0.29585 Coeff Var 119.59576
Parameter Estimates Parameter Standard
Variable DF Estimate Error t Value Pr|t| Intercept 1 -1377957 2127103 -0.65 0.5213
PTRT 1 0.202915 0.151012 1.34 0.1877 CST 1 0.988117 0.254218 3.89 0.0004
PKS 1 -4.33602 6.225737 -0.70 0.4907 PUAP 1 1.424225 1.219834 1.17 0.2509
Durbin-Watson 1.176002 Number of Observations 40
First-Order Autocorrelation 0.070798
Lampiran 3. Program Komputer Validasi Model Ekonomi Rumahtangga Petani Menggunakan SASETS Prosedur SIMNLIN Metode Newton.
options nodate nonumber; DATA BERAS;
INPUT ; CARDS ;
; data stress;
merge beras; by no; create data
NPU = JPUHREA; NTSP = JPTHTSP;
NPL= JPLHPL; NPB= JPBHB;
UPJ = UP6; NTKDK = TKDKUPJ;
NTKLK = TKLKUPJ; NTKER = NTKDK + NTKLK;
BUT = NPU + NTSP + NPL + NPB + NTKER + BL; PDP = PRDI HPDI;
PUTP = PDP - BUT; PTP = PUTP + PUTNP;
PTRT = PTP + PBNP + PBP + PL; PI = PPK + PKS;
TPRT = NPPG + PNP + PI; run;
proc simnlin data=stress dynamic simulate stat outpredict theil; endogenous GRPN PRDI JPU JPT TKDK TKLK TKER TKNP
BUT PUTP PTP PBNP PTRT PI NPPG PNP PPK PKS TAB AKE TPRT;
instruments HPDI HREA JPB HPL PUAP JAKE HTSP UP NPU NTSP NPL PDP NTKER NPL NPB BL PBP PKK UNP PL
JAK HBR NPPT PGR CST JAS JP KE; parms
A0 A1
0.000046
A2
3.17E-08
A3
9.40E-10
A4 -6.89E-09
B0 -14.8353
B1
2.190359
B2
13.5768
B3 497.472
B4
0.061583
C0 C1
-0.03383
C2
0.108447
C3
681.7279
D0 D1
-0.02111
D2 -0.01618
D3
281.3177
D4
6.75E-06
E0 -0.16701
E1
11.0912
E2 -0.02247
E3 23.07147
F0 -171.476
F1 -0.00026
F2 -0.34272
F3
1602.413
G0 -33.3652
G1
0.000173
G2 0.027848
G3
0.000013
H0 -623334
H1
4288.299
H2
69517.66
H3
49.98989
I0
923868
I1 -876.241
I2 -11022.4
I3
1.117334
I4 -434.068
J0
903596.8
J1
0.012384
J2 -0.17954
J3
848719.9
K0
309606.8
K1
0.002387
K2 -4037.75
K3 -0.02008
L0
2784103
L1
0.177213
L2 -818395
L3
3.406815
M0
73.24976
M1
6.39E-07
M2
1.99E-06
M3 -6.61001
N0 -1377957
N1
0.202915
N2
0.988117
N3 -4.33602
N4 1.424225;
GRPN =A0 + A1HPDI + A2PUAP + A3TAB + A4NPPG; PRDI =B0 + B1JPU + B2JPB + B3GRPN + B4TKER ;
JPU =C0 + C1HREA + C2TKDK + C3GRPN ; JPT =D0 + D1HTSP + D2TKLK + D3GRPN + D4PUAP ;
TKDK =E0 + E1JAKE + E2TKLK + E3GRPN; TKLK =F0 + F1UP + F2TKDK + F3GRPN ;
TKNP =G0 + G1PBNP + G2TKLK + G3PI ; PBNP =H0 + H1TKNP + H2JAKE + H3UNP ;
NPPG =I0 + I1PRDI + I2JAS + I3NPPT + I4PGR ; PPK =J0 + J1PTRT + J2NPPG + J3JAS ;
PKS =K0 + K1PTRT + K2AKE + K3PPK ; PNP =L0 + L1PTRT + L2JAS + L3PUAP ;
AKE =M0 + M1PTRT + M2NPPG + M3JAK ; TAB =N0 + N1PTRT + N2CST + N3PKS + N4PUAP ;
NPU = JPUHREA; NTSP = JPTHTSP;
NPL= JPLHPL;
NPB= JPBHB; UPJ = UP6;
TKER =TKDK + TKLK; NTKDK = TKDKUPJ;
NTKLK = TKLKUPJ; NTKER = NTKDK + NTKLK;
BUT =NPU + NTSP + NPL + NPB + NTKER + BL; PUTP =PDP - BUT;
PTP =PUTP + PUTNP; PTRT =PTP + PBNP + PBP + PL;
PI =PPK + PKS; TPRT = NPPG + PNP + PI;
run;
Lampiran 4. Hasil Validasi Model Ekonomi Rumahtangga Petani Menggunakan SASETS Prosedur SIMNLIN Metode Newton
The SAS System The SIMNLIN Procedure
Model Summary Model Variables 21
Endogenous 21 Parameters 61
Equations 21 Number of Statements 29
The SAS System The SIMNLIN Procedure
Simultaneous Simulation Data Set Options
DATA= STRESS Solution Summary
Variables Solved 21 Solution Method NEWTON
CONVERGE= 1E-8 Maximum CC 5.33E-14
Maximum Iterations 1 Total Iterations 40
Average Iterations 1 Observations Processed
Read 40 Solved 40
Variables Solved For GRPN PRDI JPU JPT TKDK TKLK TKER TKNP BUT PUTP PTP PBNP PTRT PI NPPG PNP PPK PKS
TAB AKE TPRT
The SAS System The SIMNLIN Procedure
Simultaneous Simulation Descriptive Statistics
Actual Predicted Variable N Obs N Mean Std Dev Mean Std Dev
GRPN 40 40 0.2096 0.0589 0.2080 0.0239 PRDI 40 40 488.5 361.2 485.1 192.1
JPU 40 40 84.3750 51.7661 83.2497 16.2761 JPT 40 40 35.6285 30.1702 35.2023 10.4800
TKDK 40 40 21.8000 40.0578 21.8208 10.2925 TKLK 40 40 150.8 198.4 148.2 38.6708
TKER 40 40 172.0 195.9 170.0 38.7566 TKNP 40 40 177.9 427.5 177.2 451.9
BUT 40 40 1067399 1207414 1021971 718467 PUTP 40 40 886601 1647701 932029 1506771
PTP 40 40 950751 1643914 996179 1500413 PBNP 40 40 1068000 2317314 1065164 2608138
PTRT 40 40 8496451 6439080 8539043 6269344 PI 40 40 1708075 1240126 1708052 541969
NPPG 40 40 2947850 1119354 2950838 1027227 PNP 40 40 7529475 5611313 7537021 2866294
PPK 40 40 1646550 1227528 1646541 542077 PKS 40 40 61525.0 175530 61511.7 28860.2
TAB 40 40 3909625 5277787 3918322 3365406 AKE 40 40 58.2737 12.0619 58.3036 8.7422
TPRT 40 40 12185400 5874699 12195911 2998394
Statistics of fit Mean Mean Mean Abs Mean Abs RMS RMS
Variable N Error Error Error Error Error Error R-Square GRPN 40 -0.00166 8.1094 0.0461 27.2154 0.0530 35.1421 0.1699
PRDI 40 -3.4110 33.1024 224.6 57.2069 301.4 73.0207 0.2857 JPU 40 -1.1253 54.6482 37.7203 80.6786 49.8027 134.3 0.0507
JPT 40 -0.4262 26146.4 21.5508 26177.1 28.0848 63989.7 0.1112 TKDK 40 0.0208 279.2 22.4901 305.4 38.4350 444.1 0.0558
TKLK 40 -2.5970 376.9 117.3 402.7 193.2 715.8 0.0274 TKER 40 -1.9762 153.1 112.6 175.7 188.8 309.2 0.0469
TKNP 40 -0.6613 -243.3 162.0 359.5 362.0 465.0 0.2646 BUT 40 -45427.7 75.3789 451719 95.3546 815685 168.1 0.5319
PUTP 40 45427.7 -35.8765 451719 52.3718 815685 70.4332 0.7486 PTP 40 45427.7 -17.9949 451719 56.5716 815685 99.4529 0.7475
PBNP 40 -2835.6 -143.3 741393 203.3 1550613 264.8 0.5408 PTRT 40 42592.1 -0.4224 1018676 27.0682 1714240 58.0070 0.9273
PI 40 -22.3095 44.9722 868151 70.6643 1091338 87.1997 0.2057 NPPG 40 2987.9 2.9433 389690 14.4241 463551 17.2237 0.8241
PNP 40 7546.1 34.2178 3452149 58.4293 4952181 84.7855 0.2012 PPK 40 -8.9621 46.0448 843444 71.2074 1060278 87.2983 0.2348
PKS 40 -13.3474 594.3 72841.0 612.8 166576 966.2 0.0763 TAB 40 8697.5 329.2 2196215 419.4 4299468 997.0 0.3194
AKE 40 0.0299 1.7856 6.4085 11.0934 8.5646 13.8295 0.4829 TPRT 40 10511.7 12.4957 3819226 32.0089 5204409 39.3460 0.1951
Theil Forecast Error Statistics MSE Decomposition Proportions
Corr Bias Reg Dist Var Covar Inequality Coef Variable N MSE R UM UR UD US UC U1 U
GRPN 40 0.00281 0.41 0.00 0.00 1.00 0.43 0.57 0.2437 0.1242 PRDI 40 90868.0 0.53 0.00 0.00 1.00 0.31 0.69 0.4984 0.2678
JPU 40 2480.3 0.24 0.00 0.01 0.99 0.50 0.50 0.5048 0.2715 JPT 40 788.8 0.33 0.00 0.00 1.00 0.48 0.52 0.6047 0.3378
TKDK 40 1477.3 0.24 0.00 0.00 1.00 0.58 0.42 0.8510 0.5551 TKLK 40 37312.0 0.17 0.00 0.00 1.00 0.67 0.33 0.7815 0.4827
TKER 40 35648.6 0.22 0.00 0.00 1.00 0.68 0.32 0.7296 0.4360 TKNP 40 131069 0.65 0.00 0.22 0.78 0.00 1.00 0.7903 0.3858
BUT 40 6.653E1 0.75 0.00 0.05 0.95 0.35 0.65 0.5097 0.2868 PUTP 40 6.653E1 0.87 0.00 0.01 0.99 0.03 0.97 0.4402 0.2260
PTP 40 6.653E1 0.87 0.00 0.01 0.99 0.03 0.97 0.4336 0.2225 PBNP 40 2.404E1 0.80 0.00 0.23 0.77 0.03 0.97 0.6141 0.2919
PTRT 40 2.939E1 0.96 0.00 0.00 1.00 0.01 0.99 0.1615 0.0810 PI 40 1.191E1 0.45 0.00 0.00 1.00 0.40 0.60 0.5193 0.2804
NPPG 40 2.149E1 0.91 0.00 0.00 1.00 0.04 0.96 0.1472 0.0739 PNP 40 2.452E3 0.45 0.00 0.00 1.00 0.30 0.70 0.5297 0.2846
PPK 40 1.124E2 0.49 0.00 0.00 1.00 0.41 0.59 0.5186 0.2808 PKS 40 2.775E1 0.31 0.00 0.02 0.98 0.76 0.24 0.9057 0.6618
TAB 40 1.849E3 0.57 0.00 0.01 0.99 0.19 0.81 0.6599 0.3690 AKE 40 73.3528 0.70 0.00 0.00 1.00 0.15 0.85 0.1440 0.0723
TPRT 40 2.709E3 0.45 0.00 0.01 0.99 0.30 0.70 0.3856 0.1998
Theil Relative Change Forecast Error Statistics Relative Change MSE Decomposition Proportions
Corr Bias Reg Dist Var Covar Inequality Coef Variable N MSE R UM UR UD US UC U1 U
GRPN 39 0.0766 0.83 0.00 0.00 0.99 0.13 0.87 0.5512 0.3064 PRDI 39 1.4003 0.74 0.01 0.04 0.95 0.32 0.67 0.6499 0.3984
JPU 39 4.3701 0.89 0.02 0.47 0.51 0.73 0.24 0.6137 0.4168 JPT 39 619139 0.68 0.00 0.03 0.97 0.35 0.65 0.7127 0.4484
TKDK 39 82.038 0.39 0.00 0.00 1.00 0.36 0.64 0.8737 0.5716 TKLK 39 19.603 0.88 0.07 0.09 0.84 0.01 0.92 0.4820 0.2313
TKER 39 10.176 0.57 0.02 0.03 0.95 0.11 0.87 0.8084 0.4506 TKNP 39 480.7 0.77 0.02 0.01 0.97 0.19 0.79 0.6181 0.3604
BUT 39 4.9318 0.67 0.01 0.12 0.87 0.01 0.98 0.7558 0.3820 PUTP 39 0.6096 0.99 0.02 0.03 0.94 0.01 0.97 0.1552 0.0772
PTP 39 0.4906 0.99 0.01 0.03 0.96 0.01 0.97 0.1115 0.0554 PBNP 39 104.6 0.80 0.02 0.00 0.98 0.09 0.90 0.5726 0.3150
PTRT 39 22.501 1.00 0.02 0.97 0.01 0.97 0.01 0.0708 0.0342 PI 39 1.5331 0.65 0.01 0.05 0.94 0.05 0.94 0.7431 0.3961
NPPG 39 0.0420 0.92 0.01 0.10 0.89 0.01 0.98 0.4180 0.2035 PNP 39 1.7662 0.65 0.00 0.01 0.99 0.14 0.86 0.7352 0.4199
PPK 39 1.6333 0.64 0.02 0.05 0.93 0.05 0.93 0.7573 0.4031 PKS 39 117.8 0.36 0.06 0.40 0.53 0.02 0.92 1.1484 0.5039
TAB 39 57.025 0.94 0.05 0.26 0.69 0.13 0.82 0.3841 0.1777 AKE 39 0.0299 0.79 0.00 0.01 0.99 0.18 0.82 0.6007 0.3436
TPRT 39 0.3030 0.63 0.00 0.08 0.92 0.03 0.96 0.7823 0.4176
Lampiran 5. Program Komputer Simulasi Peningkatan PUAP dan Raskin Model Ekonomi Rumahtangga Petani Menggunakan SASETS Prosedur SIMNLIN Metode Newton.
options nodate nonumber; DATA BERAS;
INPUT ; CARDS ;
; data stress;
merge beras; by no; create data
NPU = JPUHREA; NTSP = JPTHTSP;
NPL= JPLHPL; NPB= JPBHB;
UPJ = UP6; NTKDK = TKDKUPJ;
NTKLK = TKLKUPJ; NTKER = NTKDK + NTKLK;
BUT = NPU + NTSP + NPL + NPB + NTKER + BL; PDP = PRDI HPDI;
PUTP = PDP - BUT; PTP = PUTP + PUTNP;
PTRT = PTP + PBNP + PBP + PL; PI = PPK + PKS;
TPRT = NPPG + PNP + PI; PUAP = 1.30PUAP;
PGR = 1.30PGR; run;
proc simnlin data=stress dynamic simulate stat outpredict theil; endogenous GRPN PRDI JPU JPT TKDK TKLK TKER TKNP
BUT PUTP PTP PBNP PTRT PI NPPG PNP PPK PKS TAB AKE TPRT;
instruments HPDI HREA JPB HPL PUAP JAKE HTSP UP NPU NTSP NPL PDP NTKER NPL NPB BL PBP PKK UNP PL
JAK HBR NPPT PGR CST JAS JP KE; parms
A0 A1
0.000046
A2
3.17E-08
A3
9.40E-10
A4 -6.89E-09
B0 -14.8353
B1
2.190359
B2
13.5768
B3 497.472
B4
0.061583
C0 C1
-0.03383
C2
0.108447
C3
681.7279
D0 D1
-0.02111
D2 -0.01618
D3
281.3177
D4
6.75E-06
E0 -0.16701
E1
11.0912
E2 -0.02247
E3 23.07147
F0 -171.476
F1 -0.00026
F2 -0.34272
F3
1602.413
G0 -33.3652
G1
0.000173
G2 0.027848
G3
0.000013
H0 -623334
H1
4288.299
H2
69517.66
H3
49.98989
I0
923868
I1 -876.241
I2 -11022.4
I3
1.117334
I4 -434.068
J0
903596.8
J1
0.012384
J2 -0.17954
J3
848719.9
K0
309606.8
K1
0.002387
K2 -4037.75
K3 -0.02008
L0
2784103
L1
0.177213
L2 -818395
L3
3.406815
M0
73.24976
M1
6.39E-07
M2
1.99E-06
M3 -6.61001
N0 -1377957
N1
0.202915
N2
0.988117
N3 -4.33602
N4 1.424225;
GRPN =A0 + A1HPDI + A2PUAP + A3TAB + A4NPPG; PRDI =B0 + B1JPU + B2JPB + B3GRPN + B4TKER ;
JPU =C0 + C1HREA + C2TKDK + C3GRPN ;
JPT =D0 + D1HTSP + D2TKLK + D3GRPN + D4PUAP ;
TKDK =E0 + E1JAKE + E2TKLK + E3GRPN; TKLK =F0 + F1UP + F2TKDK + F3GRPN ;
TKNP =G0 + G1PBNP + G2TKLK + G3PI ; PBNP =H0 + H1TKNP + H2JAKE + H3UNP ;
NPPG =I0 + I1PRDI + I2JAS + I3NPPT + I4PGR ; PPK
=J0 + J1PTRT + J2NPPG + J3JAS ; PKS
=K0 + K1PTRT + K2AKE + K3PPK ; PNP
=L0 + L1PTRT + L2JAS + L3PUAP ; AKE
=M0 + M1PTRT + M2NPPG + M3JAK ; TAB
=N0 + N1PTRT + N2CST + N3PKS + N4PUAP ; NPU = JPUHREA;
NTSP = JPTHTSP; NPL= JPLHPL;
NPB= JPBHB; UPJ = UP6;
TKER =TKDK + TKLK; NTKDK = TKDKUPJ;
NTKLK = TKLKUPJ; NTKER = NTKDK + NTKLK;
BUT =NPU + NTSP + NPL + NPB + NTKER + BL; PUTP =PDP - BUT;
PTP =PUTP + PUTNP; PTRT =PTP + PBNP + PBP + PL;
PI =PPK + PKS; TPRT = NPPG + PNP + PI;
run;
Lampiran 6. Hasil Simulasi Peningkatan PUAP dan Raskin Model Ekonomi Rumahtangga Petani Menggunakan SASETS Prosedur SIMNLIN Metode Newton.
The SAS System The SIMNLIN Procedure
Model Summary Model Variables 21
Endogenous 21 Parameters 61
Equations 21 Number of Statements 29
The SAS System The SIMNLIN Procedure
Simultaneous Simulation Data Set Options
DATA= STRESS Solution Summary
Variables Solved 21 Solution Method NEWTON
CONVERGE= 1E-8 Maximum CC 3.21E-14
Maximum Iterations 1 Total Iterations 40
Average Iterations 1 Observations Processed
Read 40 Solved 40
Variables Solved For GRPN PRDI JPU JPT TKDK TKLK TKER TKNP BUT PUTP PTP PBNP PTRT PI NPPG PNP PPK PKS
TAB AKE TPRT
The SAS System The SIMNLIN Procedure
Simultaneous Simulation Descriptive Statistics
Actual Predicted Variable N Obs N Mean Std Dev Mean StdDev
GRPN 40 40 0.2096 0.0589 0.2209 0.0303 PRDI 40 40 488.5 361.2 512.0 201.3
JPU 40 40 84.3750 51.7661 92.0230 20.6564 JPT 40 40 35.6285 30.1702 41.0894 13.4989
TKDK 40 40 21.8000 40.0578 21.6527 10.2864 TKLK 40 40 150.8 198.4 168.9 48.7030
TKER 40 40 172.0 195.9 190.5 48.8571 TKNP 40 40 177.9 427.5 179.7 451.8
BUT 40 40 1067399 1207414 1130733 849078 PUTP 40 40 886601 1647701 823267 1564219
PTP 40 40 950751 1643914 887417 1557159 PBNP 40 40 1068000 2317314 1075745 2607442
PTRT 40 40 8496451 6439080 8440862 6255066 PI 40 40 1708075 1240126 1712651 541950
NPPG 40 40 2947850 1119354 2919467 1028013 PNP 40 40 7529475 5611313 8829117 3500178
PPK 40 40 1646550 1227528 1650957 542046 PKS 40 40 61525.0 175530 61694.0 28868.2
TAB 40 40 3909625 5277787 4445046 3468656 AKE 40 40 58.2737 12.0619 58.1784 8.7403
TPRT 40 40 12185400 5874699 13461235 3592576
Statistics of fit Mean Mean Mean Abs Mean Abs RMS RMS
Variable N Error Error Error Error Error Error R-Square GRPN 40 0.0112 14.4453 0.0440 27.5314 0.0545 38.8039 0.1230
PRDI 40 23.4868 40.6250 235.8 62.5762 304.4 80.0798 0.2714 JPU 40 7.6480 69.0691 41.0770 90.7665 50.9264 147.8 0.0074
JPT 40 5.4609 29903.0 22.9629 29926.2 28.7430 73788.6 0.0691 TKDK 40 -0.1473 276.3 22.3991 302.7 38.4374 441.6 0.0557
TKLK 40 18.1253 430.1 122.6 449.8 194.5 793.3 0.0143 TKER 40 18.5780 178.8 119.7 196.5 190.1 342.4 0.0334
TKNP 40 1.8059 -226.3 161.4 353.3 362.2 455.6 0.2638 BUT 40 63334.3 91.5245 457951 106.9 797637 186.4 0.5524
PUTP 40 -63334.3 -48.5476 457951 57.2895 797637 80.1160 0.7596 PTP 40 -63334.3 -27.2761 457951 62.4628 797637 111.0 0.7585
PBNP 40 7744.7 -136.0 737290 199.0 1551417 260.4 0.5403 PTRT 40 -55589.7 -14.5975 1026155 39.7259 1706330 119.8 0.9280
PI 40 4576.4 45.3904 868970 70.9478 1090968 87.5746 0.2062 NPPG 40 -28382.6 1.6942 387771 14.1198 462363 16.7351 0.8250
PNP 40 1299642 55.7299 3880414 72.5343 5164481 105.3 0.1312 PPK 40 4407.4 46.4683 843806 71.4397 1059860 87.6770 0.2354
PKS 40 169.0 596.4 72952.2 614.9 166593 969.3 0.0761 The SAS System
The SIMNLIN Procedure Simultaneous Simulation
Statistics of fit Mean Mean Mean Abs Mean Abs RMS RMS
Variable N Error Error Error Error Error Error R-Square TAB 40 535421 453.1 2437161 527.2 4335070 1277.6 0.3080
AKE 40 -0.0953 1.5623 6.3700 11.0097 8.5614 13.7747 0.4833 TPRT 40 1275835 23.5745 4134075 37.4896 5390610 47.7936 0.1364
Theil Forecast Error Statistics MSE Decomposition Proportions
Corr Bias Reg Dist Var Covar Inequality Coef Variable N MSE R UM UR UD US UC U1 U
GRPN 40 0.00297 0.41 0.04 0.01 0.95 0.27 0.69 0.2505 0.1237 PRDI 40 92687.3 0.53 0.01 0.00 0.99 0.27 0.72 0.5033 0.2638
JPU 40 2593.5 0.24 0.02 0.03 0.95 0.36 0.61 0.5162 0.2640 JPT 40 826.2 0.34 0.04 0.01 0.95 0.33 0.64 0.6189 0.3207
TKDK 40 1477.4 0.24 0.00 0.00 1.00 0.58 0.42 0.8511 0.5564 TKLK 40 37814.3 0.17 0.01 0.01 0.99 0.58 0.41 0.7868 0.4600
TKER 40 36153.5 0.21 0.01 0.00 0.99 0.58 0.41 0.7347 0.4176 TKNP 40 131216 0.65 0.00 0.22 0.78 0.00 1.00 0.7907 0.3857
BUT 40 6.362E11 0.75 0.01 0.00 0.99 0.20 0.80 0.4985 0.2652 PUTP 40 6.362E11 0.88 0.01 0.02 0.97 0.01 0.98 0.4305 0.2214
PTP 40 6.362E11 0.87 0.01 0.02 0.97 0.01 0.98 0.4240 0.2181 PBNP 40 2.407E12 0.80 0.00 0.23 0.77 0.03 0.97 0.6144 0.2919
PTRT 40 2.912E12 0.96 0.00 0.00 1.00 0.01 0.99 0.1608 0.0810 PI 40 1.19E12 0.45 0.00 0.00 1.00 0.40 0.60 0.5191 0.2800
NPPG 40 2.138E11 0.91 0.00 0.00 1.00 0.04 0.96 0.1469 0.0741 PNP 40 2.667E13 0.46 0.06 0.03 0.91 0.16 0.77 0.5524 0.2743
PPK 40 1.123E12 0.49 0.00 0.00 1.00 0.41 0.59 0.5184 0.2804 PKS 40 2.775E10 0.31 0.00 0.02 0.98 0.76 0.24 0.9058 0.6614
TAB 40 1.879E13 0.57 0.02 0.01 0.97 0.17 0.81 0.6654 0.3575 AKE 40 73.2977 0.70 0.00 0.00 1.00 0.15 0.85 0.1439 0.0724
TPRT 40 2.906E13 0.46 0.06 0.03 0.92 0.17 0.77 0.3994 0.1966
Theil Relative Change Forecast Error Statistics Relative Change MSE Decomposition Proportions
Corr Bias Reg Dist Var Covar Inequality Coef Variable N MSE R UM UR UD US UC U1 U
GRPN 39 0.0785 0.83 0.03 0.01 0.97 0.05 0.92 0.5580 0.2932 PRDI 39 1.3541 0.74 0.00 0.02 0.97 0.29 0.71 0.6391 0.3821
JPU 39 3.6115 0.91 0.01 0.46 0.54 0.71 0.29 0.5579 0.3613 JPT 39 598993 0.68 0.00 0.00 1.00 0.23 0.77 0.7010 0.4172
TKDK 39 82.0428 0.39 0.00 0.00 1.00 0.37 0.63 0.8737 0.5726 TKLK 39 24.6941 0.90 0.15 0.26 0.59 0.11 0.74 0.5410 0.2408
The SAS System The SIMNLIN Procedure
Simultaneous Simulation Theil Relative Change Forecast Error Statistics
Relative Change MSE Decomposition Proportions Corr Bias Reg Dist Var Covar Inequality Coef
Variable N MSE R UM UR UD US UC U1 U TKER 39 10.2228 0.60 0.05 0.05 0.90 0.06 0.89 0.8102 0.4291
TKNP 39 479.7 0.77 0.02 0.01 0.97 0.19 0.79 0.6175 0.3598 BUT 39 5.2064 0.68 0.04 0.16 0.80 0.00 0.96 0.7765 0.3765
PUTP 39 0.6831 0.99 0.07 0.00 0.92 0.00 0.93 0.1643 0.0826 PTP 39 0.5285 0.99 0.05 0.00 0.95 0.00 0.95 0.1157 0.0579
PBNP 39 104.4 0.80 0.01 0.00 0.99 0.09 0.90 0.5722 0.3146 PTRT 39 15.3685 1.00 0.02 0.97 0.01 0.97 0.01 0.0585 0.0284
PI 39 1.5343 0.65 0.01 0.05 0.94 0.05 0.94 0.7434 0.3957 NPPG 39 0.0414 0.92 0.00 0.09 0.91 0.01 0.99 0.4151 0.2034
PNP 39 1.9847 0.64 0.05 0.06 0.89 0.04 0.91 0.7793 0.4044 PPK 39 1.6350 0.64 0.02 0.05 0.93 0.05 0.93 0.7576 0.4028
PKS 39 118.3 0.36 0.06 0.40 0.53 0.02 0.92 1.1507 0.5041 TAB 39 92.5171 0.93 0.09 0.45 0.46 0.30 0.61 0.4893 0.2126
AKE 39 0.0300 0.79 0.00 0.01 0.99 0.18 0.82 0.6010 0.3441 TPRT 39 0.3532 0.63 0.06 0.15 0.79 0.00 0.94 0.8446 0.4130
Lampiran 7. Hasil Analisis Ketahanan Pangan Rumahtangga Petani Sampel
No KE
JP AKE
AKP PTJB
JBBB PGRB
KSPB KBRB
NPPGB PTRTB
RPPB JAK
STATUS KETAHANAN
PANGAN
1 1031.25
15.62 51.56
30.04 10.00
15.00 5.00
30.00 40.00
264500.00 132729.20
199.28 4
TTP 2
1316.85 15.62
65.84 30.04
10.00 26.00
4.00 40.00
40.00 497500.00
563868.10 88.23
4 TTP
3 1163.20
18.64 58.16
35.85 10.00
15.00 5.00
30.00 40.00
415500.00 651270.80
63.80 4
TTP 4
1352.10 24.15
67.61 46.44
66.67 15.00
4.70 86.37
30.00 348900.00
454472.20 76.77
3 TTP
5 1475.70
17.85 73.79
34.33 12.50
12.50 5.00
30.00 20.00
278000.00 548638.90
50.67 2
TP 6
1091.50 21.00
54.58 40.39
32.50 2.50
4.00 39.00
40.00 165200.00
664888.90 24.85
4 TTP
7 1326.00
21.00 66.30
40.39 25.00
8.33 4.00
37.33 30.00
206033.30 1492306.00
13.81 3
TP 8
1066.50 21.00
53.33 40.39
40.00 8.33
5.00 53.33
30.00 281033.30
279302.80 100.62
3 TTP
9 1066.50
21.00 53.33
40.39 25.00
10.00 5.00
40.00 40.00
230500.00 182166.70
126.53 4
TTP 10
1008.60 8.40
50.43 16.15
25.00 10.00
5.00 40.00
60.00 170500.00
1142343.00 14.93
6 TTP
11 1190.10
17.85 59.51
34.33 12.50
13.50 4.00
30.00 40.00
290000.00 519083.30
55.87 4
TTP 12
1066.50 21.00
53.33 40.39
29.17 4.17
5.00 38.33
40.00 177666.70
472833.30 37.57
4 TTP
13 888.00
21.00 44.40
40.39 100.00
3.33 5.00
108.33 50.00
231833.30 929500.00
24.94 5
TTP 14
1066.50 21.00
53.33 40.39
33.33 10.00
5.00 48.33
40.00 220000.00
358833.30 61.31
4 TTP
15 1378.40
24.15 68.92
46.44 50.00
5.00 10.00
65.00 30.00
246000.00 545402.80
45.10 3
TP 16
1040.40 21.00
52.02 40.39
17.50 7.50
5.00 30.00
30.00 211000.00
551833.30 38.24
3 TTP
17 1106.00
16.71 55.30
32.14 83.33
0.00 5.00
88.33 70.00
513000.00 -151632.00
-338.32 7
TTP 18
1066.50 21.00
53.33 40.39
25.00 16.67
5.00 46.67
40.00 397166.70
1148333.00 34.59
4 TTP
19 861.90
21.00 43.10
40.39 40.00
8.33 5.00
53.33 50.00
206833.30 399965.30
51.71 5
TTP 20
1352.10 21.00
67.61 40.39
12.50 12.50
5.00 30.00
30.00 233000.00
-63013.90 -369.76
3 TTP
21 1091.50
21.00 54.58
40.39 85.00
0.00 6.00
91.00 40.00
117700.00 764527.80
15.40 4
TTP 22
1326.00 21.00
66.30 40.39
41.67 0.00
6.00 47.67
30.00 118000.00
1209472.00 9.76
3 TP
23 1326.00
24.15 66.30
46.44 54.17
0.00 4.00
58.17 30.00
278000.00 414333.30
67.10 3
TTP 24
1315.70 13.86
65.79 26.65
50.00 0.00
6.00 56.00
30.00 130000.00
369333.30 35.20
3 TP
25 985.50
17.85 49.28
34.33 40.00
3.33 4.50
47.83 30.00
146833.30 253194.40
57.99 3
TTP 26
933.60 16.73
46.68 32.17
33.33 6.67
5.00 45.00
50.00 257166.70
393979.20 65.27
5 TTP
27 1352.10
21.00 67.61
40.39 158.33
0.00 5.00
163.33 30.00
235000.00 1832500.00
12.82 3
TP 28
1112.10 18.64
55.61 35.85
25.00 0.00
5.00 30.00
40.00 254700.00
1198924.00 21.24
4 TTP
29 770.20
21.00 38.51
40.39 62.50
2.50 4.50
69.50 60.00
297200.00 386236.10
76.95 6
TTP 30
766.62 21.00
38.33 40.39
20.00 5.00
5.50 30.50
40.00 195500.00
-78180.60 -250.06
4 TTP
31 982.50
19.32 49.13
37.15 11.67
10.00 6.00
27.67 40.00
245000.00 -255708.00
-95.81 4
TTP 32
861.90 21.00
43.10 40.39
99.17 0.00
5.00 104.17
70.00 160500.00
971833.30 16.52
7 TTP
33 1326.00
21.00 66.30
40.39 50.00
3.33 4.00
57.33 50.00
257833.30 441069.40
58.46 5
TP 34
1167.00 27.30
58.35 52.50
33.33 10.00
5.00 48.33
40.00 330500.00
1349479.00 24.49
4 TTP
35 1157.80
24.60 57.89
47.31 20.00
10.00 6.00
36.00 40.00
289700.00 617486.10
46.92 4
TTP 36
1401.00 24.60
70.05 47.31
35.00 10.00
4.00 49.00
30.00 262500.00
336805.50 77.94
3 TTP
37 1405.80
12.00 70.29
23.08 35.00
0.00 4.00
39.00 40.00
219700.00 2673910.00
8.22 4
TP 38
1352.10 24.60
67.61 47.31
40.00 0.00
4.00 44.00
30.00 118500.00
337590.30 35.10
3 TP
39 973.50
27.30 48.68
52.50 40.00
0.00 5.00
45.00 60.00
110500.00 555909.80
19.88 6
TTP 40
2097.45 12.00
104.87 23.08
20.00 16.67
4.50 41.17
20.00 217166.70
1073431.00 20.23
2 TP
Keterangan
:
KE : Kecukupan Energi Kkal
AKE : Angka Kecukupan Energi
KSPB : Ketersediaan Pangan Per bulan Kgbulan KBRB : Kebutuhan Beras Riil Per bulan Kgbulan
NPPGB : Nilai Pengeluaran Pangan Per bulan Rpbln PTRTB : Pendapatan Rumahtangga Per bulan Rpbln
RPPB : Rasio Pengeluaran Pangan dengan Pendapatan Rumahtangga TP
: Tahan Pangan. TTP : Tidak Tahan Pangan
ABSTRACT
FANNY SEPTYA. Role of PUAP and raskin in Activity dan Food Security Agriculture Household Case in Sadang District. Supervisied by RATNA
WINANDI and SUHARNO.
The aim of this research is to descriptive performance of economic household and food security also analyze role of PUAP in paddy production and
role of raskin in food consumption so that programs can improve agriculture household food security. This research used survey method to paddy peasant that
received PUAP and raskin. To analyze performance of household food security used descriptive analysis by food availability, ratio food expenditure of total
household revenue and number of energy sufficiency indicators. And to analyze role of PUAP and raskin in agriculture household food security used agriculture
household model that consisted of 14 structural equations and 7 identities. The result indicated that paddy production used to household consumption so that for
non food and human resources investment expenditure used income from non agriculture activity. Food security problem of 75 household sampel is food
purchasing power that indicated by highly ratio food expenditure of total household revenue so that number of energy sufficiency have not been able to
fulfill. PUAP not only has increased production so that increased food availability, but also increased non food expenditure. Raskin has reduced food
expenditure but increased number of PUAP and raskin has decreased number of energy sufficiency. According to analysis result, production input subsidy will be
effectice and efisien to increased paddy production so will improve household food availability and increase peasant revenue. Number of raskin need to increase
adjusted to real rice need of household and also need high protein subsidy to increase number of energy sufficiency.
Keywords : food security, agriculture household, production, food consumption
food purchasing power
RINGKASAN
FANNY SEPTYA. Peranan PUAP dan raskin dalam Perilaku Ekonomi dan Ketahanan Pangan Rumahtangga Petani Kasus di Kecamatan Sadang, Kabupaten
Kebumen . Dibimbing oleh RATNA WINANDI dan SUHARNO
Analisis ekonomi rumahtangga petani memperhitungkan bagaimana pengaruh bantuan modal PUAP dan raskin dalam keputusan produksi dan
konsumsi yang saling terkait sehingga mendukung indikator ketahanan pangan rumahtangga petani. PUAP dan raskin telah dilaksanakan di salah satu daerah
rawan pangan Kabupaten Kebumen yakni Kecamatan Sadang sehingga pada Tahun 2012, Kecamatan Sadang mengalami perbaikan tingkat ketahanan pangan
sehingga termasuk daerah rawan pangan prioritas 5. Untuk mengetahui bagaimana PUAP dan raskin berperan dalam perbaikan kondisi ketahanan pangan Kecamatan
Sadang, perlu diidentifikasi bagaimana peran bantuan modal PUAP dan raskin dalam perilaku ekonomi rumahtangga petani sehingga mendukung kinerja
ketahanan pangan rumahtangga petani.
Tujuan penelitian ini adalah untuk menganalisis secara deskriptif karakteristik perilaku ekonomi dan tingkat ketahanan pangan rumahtangga petani
serta peran PUAP dalam peningkatan produksi padi dan peran raskin dalam pengeluaran pangan sehingga kedua program tersebut mampu mendukung
ketahanan pangan rumahtangga petani. Penelitian ini menggunakan metode survey pada petani padi penerima PUAP dan raskin. Untuk menganalisis tingkat
ketahanan pangan rumahtangga petani digunakan analisis deskriptif dengan indikator ketersediaan pangan, rasio pengeluaran pangan dengan pendapatan
rumahtangga dan angka kecukupan energi. Untuk menganalisis peran PUAP dan raskin dalam ketahanan pangan rumahtangga petani digunakan model ekonomi
rumahtangga pertanian yang terdiri dari 14 persamaan struktural dan 7 persamaan identitas yang diestimasi dengan metode 2 SLS. Simulasi kebijakan yang
dilakukan adalah peningkatan PUAP 30, peningkatan raskin 30 dan peningkatan PUAP dan raskin secara bersamaan sebesar 30 dimana dari ketiga
alternatif kebijakan tersebut berdampak pada perilaku ekonomi dan ketahanan pangan rumahtangga petani.
Dari hasil analisis penelitian secara deskriptif, keterkaitan keputusan ekonomi rumahtangga petani sampel ditunjukan dengan keputusan penggunaan
produksi padi untuk konsumsi pangan rumahtangga, sedangkan kegiatan produktif yang digunakan untuk pengeluaran non pangan, investasi sumberdaya
manusia dan tabungan bersumber dari pendapatan non pertanian. Tingkat ketahanan pangan rumahtangga disimpulkan bahwa 75 rumahtangga petani
sampel tidak tahan pangan. Indikator ketahanan pangan yang tidak terpenuhi oleh rumahtangga tidak tahan pangan adalah indikator daya beli yang diindikasikan
dengan tingginya porsi pengeluaran pangan dalam pendapatan rumahtangga sehingga angka kecukupan energi anggota keluarga tidak dapat terpenuhi.
Hasil analisis model perilaku ekonomi rumahtangga mengindikasikan bahwa PUAP berpengaruh nyata dalam peningkatan luas garapan sehingga
meningkatkan produksi padi. Hal ini akan mendukung indikator ketersediaan pangan bagi rumahtangga petani subsisten. Luas garapan juga berpengaruh nyata
dan positif pada penggunaan input produksi yakni penggunaan pupuk dan tenaga
kerja luar keluarga. Oleh karena peningkatan produksi padi digunakan untuk kebutuhan konsumsi pangan rumahtangga, maka petani meningkatakan alokasi
waktu berburuh non pertanian untuk meningkatkan pendapatan rumahtangga dari pendapatan berburuh non pertanian guna memenuhi kebutuhan konsumsi investasi
sumberdaya manusia.
Peningkatan produksi padi bagi rumahtangga petani subsisten akan mengurangi jumlah beras yang dibeli di pasar sehingga hal ini mengurangi
pengeluaran pangan. Di sisi lain, pengeluaran protein berpengaruh nyata dan positif pada pengeluaran pangan rumahtangga. Selain digunakan untuk kegiatan
produksi, PUAP juga digunakan untuk konsumsi non pangan sehingga peningkatan PUAP berpengaruh nyata dan positif terhadap pengeluaran non
pangan. Angka kecukupan energi sebagai indikator hasil ketahanan pangan dipengaruhi secara nyata oleh pendapatan dan jumlah anggota keluarga dimana
peningkatan pendapatan rumahtangga dapat meningkatkan angka kecukupan energi karena hal ini menunjukan perbaikan daya beli rumahtangga terhadap
pangan. Sementara peningkatan jumlah anggota keluarga dapat menurunkan angka kecukupan energi karena mengindikasikan peningkatan kebutuhan
konsumsi energi yang harus dipenuhi dengan pendapatan yang dimiliki. Peningkatan angka kecukupan energi akan mengurangi pengeluaran kesehatan.
Hal ini mengindikasikan bahwa ketahanan pangan menentukan kualitas hidup sehat rumahtangga. Pada perilaku menabung, jumlah asset produktif berpengaruh
nyata pada peningkatan jumlah tabungan rumahtangga.
Hasil simulasi peningkatan PUAP mengindikasikan bahwa peningkatan PUAP 30 meningkatkan produksi padi 5,5 yang diikuti dengan peningkatan
penggunaan input-input produksi 10-16. Peningkatan produksi tersebut mendukung indikator ketersediaan pangan bagi rumahtangga petani sehingga
mengurangi pengeluaran pangan hanya sebesar 0,7. Peningkatan ketersediaan pangan beras tidak diikuti dengan peningkatan angka kecukupan energi karena
terjadi penurunan angka kecukupan energi sebesar 0,18. Peningkatan raskin 30 berpengaruh sangat kecil pada kegiatan produksi dan mengurangi
pengeluaran pangan sebesar 0,26, namun masih terjadi penurunan pada angka kecukupan energi yakni sebesar 0,03. Peningkatan PUAP dan raskin 30 secara
bersamaan mampu meningkatkan produksi 5,54 dan penurunan pengeluaran pangan sebesar 1,06, namun terjadi penurunan pendapatan rumahtangga yakni
sebesar 1,15. Sementara itu, terjadi peningkatan konsumsi non pangan sebesar 17,14. Oleh karena bantuan dari program penanggulangan kemiskinan tersebut
tidak digunakan sepenuhnya untuk kegiatan produktif yang dapat meningkatkan daya beli pangan terjadi penurunan angka kecukupan energi sebesar 0,21.
Berdasarkan hasil analisis, subsidi input produksi natura akan lebih efektif dan efisien untuk meningkatkan produksi padi sehingga akan meningkatkan
ketersediaan pangan dan pendapatan petani padi. Jumlah pagu raskin perlu disesuaikan dengan kebutuhan beras riil anggota rumahtangga. Diperlukan subsidi
protein bernutrisi tinggi untuk meningkatkan angka kecukupan energi.
Kata Kunci: ketahanan pangan, ekonomi rumahtangga petani, produksi, konsumsi pangan, daya beli pangan.