Lampiran 2. Hasil Analisis Efisiensi Teknis Penggunaan Pupuk pada Kubis Bunga dengan Menggunakan Frontier
Output from the program FRONTIER (Version 4.1c)
instruction file = terminal data file = kbunga2.txt
Error Components Frontier (see B&C 1992) The model is a production function
The dependent variable is logged
the ols estimates are :
coefficient standard-error t-ratio
beta 0 0.92847007E+01 0.97371410E+00 0.95353459E+01 beta 1 -0.90486142E-01 0.15032059E+00 -0.60195441E+00 sigma-squared 0.50613133E-01
log likelihood function = 0.41558474E+01
the estimates after the grid search were :
beta 0 0.93245333E+01 beta 1 -0.90486142E-01 sigma-squared 0.49845671E-01 gamma 0.50000000E-01 mu is restricted to be zero eta is restricted to be zero
iteration = 0 func evals = 20 llf = 0.41534686E+01
0.93245333E+01-0.90486142E-01 0.49845671E-01 0.50000000E-01 gradient step
iteration = 5 func evals = 82 llf = 0.41552714E+01
0.93001347E+01-0.89060270E-01 0.48844630E-01 0.19896535E-01 iteration = 10 func evals = 169 llf = 0.41557122E+01
0.92963826E+01-0.89880951E-01 0.48483387E-01 0.76795660E-02 iteration = 15 func evals = 260 llf = 0.41558062E+01
0.92976571E+01-0.90814751E-01 0.48381277E-01 0.37400678E-02 iteration = 20 func evals = 366 llf = 0.41558321E+01
0.92942767E+01-0.90729811E-01 0.48328384E-01 0.20800485E-02 iteration = 25 func evals = 473 llf = 0.41558406E+01
0.92909240E+01-0.90515510E-01 0.48295611E-01 0.11642015E-02 iteration = 30 func evals = 582 llf = 0.41558446E+01
0.92894035E+01-0.90491248E-01 0.48280869E-01 0.70296009E-03 iteration = 35 func evals = 692 llf = 0.41558462E+01
0.92881178E+01-0.90466119E-01 0.48271095E-01 0.40647642E-03 iteration = 40 func evals = 786 llf = 0.41558467E+01
0.92868379E+01-0.90475667E-01 0.48263616E-01 0.15710852E-03 iteration = 50 func evals = 994 llf = 0.41558472E+01
0.92862804E+01-0.90478859E-01 0.48261506E-01 0.85761481E-04 iteration = 51 func evals = 1002 llf = 0.41558472E+01
0.92862804E+01-0.90478859E-01 0.48261506E-01 0.85761482E-04
the final mle estimates are :
coefficient standard-error t-ratio
beta 0 0.92862804E+01 0.95513210E+00 0.97225090E+01 beta 1 -0.90478859E-01 0.12560763E+00 -0.72032932E+00 sigma-squared 0.48261506E-01 0.10748162E-01 0.44902099E+01 gamma 0.85761482E-04 0.74630451E-01 0.11491486E-02 mu is restricted to be zero
eta is restricted to be zero
log likelihood function = 0.41558472E+01
LR test of the one-sided error = 0.451275292E+02 with number of restrictions = 1
[note that this statistic has a mixed chi-square distribution]
number of iterations = 51
(maximum number of iterations set at : 100)
number of cross-sections = 43
number of time periods = 1
total number of observations = 43
thus there are: 0 obsns not in the panel
covariance matrix :
0.91227733E+00 -0.87263769E-01 -0.16101983E-03 0.38545930E-01 -0.87263769E-01 0.15777277E-01 0.21367388E-03 0.17211083E-02 -0.16101983E-03 0.21367388E-03 0.11552300E-03 0.13543686E-03 0.38545930E-01 0.17211083E-02 0.13543686E-03 0.55697043E-02 technical efficiency estimates :
6 0.99838367E+00 mean efficiency = 0.99837881E+00
Lampiran 4. Hasil Analisis Efisiensi Teknis Penggunaan Pupuk pada Kubis dengan Menggunakan Frontier
Output from the program FRONTIER (Version 4.1c)
instruction file = terminal data file = kubis2.txt
Error Components Frontier (see B&C 1992) The model is a production function
The dependent variable is logged
the ols estimates are :
coefficient standard-error t-ratio
beta 0 0.41203495E+01 0.23884521E+01 0.17251129E+01 beta 1 0.68578412E+00 0.37296380E+00 0.18387418E+01 sigma-squared 0.41795538E-01
log likelihood function = 0.44244919E+01
the estimates after the grid search were :
beta 0 0.41555165E+01 beta 1 0.68578412E+00 sigma-squared 0.38852704E-01
7 Mamak Petro 35 49 SD 4
8 Hendra Sembiring 8 38 SMA 2
9 Rolianta Br Sinuhaji 7 42 STM 1
10 Ahmadi Sukapiring 5 48 SMA 2
11 Lekson Br Tarigan 4 59 SD 3
12 Dolat J. Ginting 11 41 S1 2
13 Sarjani Sembiring 4 30 SMP 3
14 Diamon Bukit 6 27 SMP 2
15 Tommi 20 45 SMP 4
16 Rela Ginting 36 56 SMA 2
17 Armut Br Ginting 14 46 SMA 1
18 Margareta Pandia 20 52 SD 4
19 B. Tarigan 7 34 SMP 3
gamma 0.50000000E-01 mu is restricted to be zero eta is restricted to be zero
iteration = 0 func evals = 20 llf = 0.44135626E+01
0.41555165E+01 0.68578412E+00 0.38852704E-01 0.50000000E-01 gradient step
iteration = 5 func evals = 66 llf = 0.44233333E+01
0.41499697E+01 0.68365001E+00 0.37780841E-01 0.92670158E-02 iteration = 10 func evals = 167 llf = 0.44244119E+01
0.41244564E+01 0.68610175E+00 0.37577950E-01 0.15732328E-02 iteration = 15 func evals = 271 llf = 0.44244774E+01
0.41202560E+01 0.68636365E+00 0.37611530E-01 0.54269376E-03 iteration = 20 func evals = 376 llf = 0.44244892E+01
0.41240107E+01 0.68554286E+00 0.37616181E-01 0.18620835E-03 iteration = 25 func evals = 469 llf = 0.44244911E+01
0.41210118E+01 0.68589885E+00 0.37615449E-01 0.80039171E-04 iteration = 30 func evals = 577 llf = 0.44244917E+01
0.41213495E+01 0.68576924E+00 0.37617525E-01 0.33658171E-04 iteration = 35 func evals = 684 llf = 0.44244918E+01
0.41209642E+01 0.68578973E+00 0.37616408E-01 0.17667934E-04 iteration = 40 func evals = 779 llf = 0.44244919E+01
0.41206752E+01 0.68578958E+00 0.37616694E-01 0.54371723E-05 iteration = 41 func evals = 797 llf = 0.44244919E+01
0.41206718E+01 0.68578953E+00 0.37616711E-01 0.52981596E-05 The final mle estimates are :
coefficient standard-error t-ratio
beta 0 0.41206718E+01 0.21339311E+01 0.19310238E+01 beta 1 0.68578953E+00 0.30573054E+00 0.22431175E+01 sigma-squared 0.37616711E-01 0.12584465E-01 0.29891388E+01 gamma 0.52981596E-05 0.18684141E-01 0.28356453E-03 mu is restricted to be zero
eta is restricted to be zero
log likelihood function = 0.44244919E+01
LR test of the one-sided error = 0.4935062E+01 with number of restrictions = 1
[note that this statistic has a mixed chi-square distribution]
number of iterations = 41
(maximum number of iterations set at : 100)
number of cross-sections = 20
total number of observations = 20
thus there are: 0 obsns not in the panel
covariance matrix :
0.45536621E+01 -0.63328903E+00 -0.74676150E-02 0.18217557E-01 -0.63328903E+00 0.93471162E-01 0.36356294E-03 -0.13343168E-02 -0.74676150E-02 0.36356294E-03 0.15836875E-03 -0.18797657E-03 0.18217557E-01 -0.13343168E-02 -0.18797657E-03 0.34909712E-03 technical efficiency estimates : mean efficiency = 0.99964390E+00
Lampiran 6. Hasil Analisis Efisiensi Teknis Penggunaan Pupuk pada Wortel dengan Menggunakan Frontier
Output from the program FRONTIER (Version 4.1c)
instruction file = terminal data file = wortel2.txt
Error Components Frontier (see B&C 1992) The model is a production function
The dependent variable is logged
the ols estimates are :
coefficient standard-error t-ratio
beta 0 0.65305367E+01 0.10558076E+01 0.61853476E+01 beta 1 0.36092867E+00 0.20124336E+00 0.17934936E+01 sigma-squared 0.33424173E-01
log likelihood function = 0.58289771E+01
the estimates after the grid search were :
7 Robin 9 40 SMA 3
8 Fitri Br Barus 8 30 SMA 1
9 Hendra Sembiring 8 38 SMA 2
10 Reksa Ginting 5 66 SMA 4
11 Ulina Br Sinuhaji 25 40 SMA 5
12 Irawati Br Ginting 8 29 SMA 3
13 Ridwan Parangin-Angin 12 40 SMP 3
14 Supardi Pandia 13 39 SMA 6
15 Rolianta Br Sinuhaji 7 42 STM 1
16 Edi Syahputra Sembiring 4 34 SMA 1
beta 0 0.65616754E+01 beta 1 0.36092867E+00 sigma-squared 0.30461539E-01 gamma 0.50000000E-01
0.65616754E+01 0.36092867E+00 0.30461539E-01 0.50000000E-01 gradient step
iteration = 5 func evals = 82 llf = 0.58283720E+01
0.65406749E+01 0.36202889E+00 0.29710860E-01 0.13323183E-01 iteration = 10 func evals = 184 llf = 0.58289173E+01
0.65365943E+01 0.36118280E+00 0.29533496E-01 0.28517551E-02 iteration = 15 func evals = 272 llf = 0.58289660E+01
0.65345644E+01 0.36091369E+00 0.29503519E-01 0.78963395E-03 iteration = 20 func evals = 377 llf = 0.58289746E+01
0.65332090E+01 0.36090344E+00 0.29497272E-01 0.33567707E-03 iteration = 25 func evals = 483 llf = 0.58289762E+01
0.65324855E+01 0.36090929E+00 0.29497128E-01 0.18187694E-03 iteration = 30 func evals = 573 llf = 0.58289770E+01
0.65314715E+01 0.36092271E+00 0.29495277E-01 0.43396786E-04 iteration = 35 func evals = 648 llf = 0.58289771E+01
0.65312182E+01 0.36093906E+00 0.29491805E-01 0.28503070E-04 iteration = 36 func evals = 651 llf = 0.58289771E+01
0.65312182E+01 0.36093906E+00 0.29491805E-01 0.28503069E-04
the final mle estimates are :
coefficient standard-error t-ratio
beta 0 0.65312182E+01 0.11383015E+01 0.57376872E+01 beta 1 0.36093906E+00 0.17432521E+00 0.20704926E+01 sigma-squared 0.29491805E-01 0.89833335E-02 0.32829467E+01 gamma 0.28503069E-04 0.41731250E-01 0.68301498E-03 mu is restricted to be zero
eta is restricted to be zero
log likelihood function = 0.58289771E+01
LR test of the one-sided error = 0.60275292E+02 with number of restrictions = 1
number of iterations = 36
(maximum number of iterations set at : 100)
number of cross-sections = 17
number of time periods = 1
total number of observations = 17
thus there are: 0 obsns not in the panel
covariance matrix :
0.12957304E+01 -0.17957990E+00 0.99145237E-04 0.28736304E-01 -0.17957990E+00 0.30389281E-01 0.27913850E-03 -0.15218485E-02 0.99145237E-04 0.27913850E-03 0.80700281E-04 0.12060702E-03 0.28736304E-01 -0.15218485E-02 0.12060702E-03 0.17414972E-02
technical efficiency estimates :
firm eff.-est.
1 0.99926865E+00 2 0.99926917E+00 3 0.99926842E+00 4 0.99926594E+00 5 0.99927165E+00 6 0.99926928E+00 7 0.99926784E+00 8 0.99926874E+00 9 0.99926923E+00 10 0.99926764E+00 11 0.99926985E+00 12 0.99927196E+00 13 0.99926687E+00 14 0.99927262E+00 15 0.99926682E+00 16 0.99926855E+00 17 0.99926778E+00
Regresi Linear Berganda Faktor-Faktor Yang Mempengaruhi
Penggunaan Pupuk Pada Tanaman Sayuran
Lampiran 7. Hasil Analisis Statistik Kubis Bunga
Descriptive Statistics
Mean Std. Deviation N
Dosis Pupuk (Y) 6.6372E2 139.99614 43
Harga Pupuk (X1) 4.2508E6 1.15015E6 43
Harga Kubis Bunga (X2) 4.2953E3 463.91373 43
Pengalaman Bertani (X3) 11.3488 8.73113 43
Variables Entered/Removedb
Model
Variables
Entered
Variables
Removed Method
1 Pengalaman
Bertani (X3),
Harga Pupuk
(X1), Harga
Kubis Bunga
(X2)a
. Enter
a. All requested variables entered.
b. Dependent Variable: Dosis Pupuk (Y)
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
Change Statistics
R Square Change F Change df1 df2
Sig. F
1 .732a .536 .500 98.99632 .536 14.998 3 39 .000 a. Predictors: (Constant), Pengalaman Bertani (X3), Harga Pupuk (X1), Harga Kubis Bunga (X2)
b. Dependent Variable: Dosis Pupuk Y
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 440944.035 3 146981.345 14.998 .000a
Residual 382210.617 39 9800.272
Total 823154.651 42
a. Predictors: (Constant), Pengalaman Bertani (X3), Harga Pupuk (X1), Harga Kubis Bunga (X2)
b. Dependent Variable: Dosis Pupuk (Y)
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 326.886 157.927 2.070 .045
Harga Pupuk (X1) 8.873E-5 .000 .729 6.632 .000
Harga Kubis Bunga (X2) -.009 .034 -.031 -.278 .783
Pengalaman Bertani (X3) -.010 1.792 .000 -.006 .996
Lampiran 8. Hasil Analisis Statistik Kubis
Variables Entered/Removedb
Model
Variables
Entered
Variables
Removed Method
1 Pengalaman
Bertani (X3),
Harga Pupuk
(X1), Harga
Kubis (X2)a
. Enter
a. All requested variables entered.
b. Dependent Variable: Dosis Pupuk (Y)
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
Change Statistics
R Square Change F Change df1 df2 Sig. F Change
1 .596a .355 .234 70.75871 .355 2.940 3 16 .065
a. Predictors: (Constant), Pengalaman Bertani (X3), Harga Pupuk (X1), Harga Kubis
(X2)
b. Dependent Variable: Dosis Pupuk (Y)
ANOVAb
Model Sum of Squares df Mean Square F Sig.
Descriptive Statistics
Mean Std. Deviation N
Dosis Pupuk (Y) 6.0825E2 80.87149 20
Harga Pupuk (X1) 3.8888E6 7.35078E5 20
Harga Kubis (X2) 1.0400E3 354.51969 20
1 Regression 44155.028 3 14718.343 2.940 .065a
Residual 80108.722 16 5006.795
Total 124263.750 19
a. Predictors: (Constant), Pengalaman Bertani (X3), Harga Pupuk (X1), Harga Kubis (X2)
b. Dependent Variable: Dosis Pupuk (Y)
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 357.514 107.465 3.327 .004
Harga Pupuk (X1) 5.976E-5 .000 .543 2.653 .017
Harga Kubis (X2) -.009 .056 -.037 -.151 .882
Pengalaman Bertani (X3) 1.864 1.961 .233 .950 .356
a. Dependent Variable: Dosis Pupuk (Y)
Lampiran 9. Hasil Analisis Statistik Wortel
Descriptive Statistics
Mean Std. Deviation N
Dosis Pupuk (Y) 1.9382E2 48.15760 17
Harga Pupuk (X1) 1.7005E6 4.04216E5 17
Harga Wortel (X2) 2.4706E3 1012.27757 17
Pengalaman Bertani (X3) 12.6471 7.36496 17
Model
a. All requested variables entered.
b. Dependent Variable: Dosis Pupuk (Y)
Model Summaryb
a. Predictors: (Constant), Pengalaman Bertani (X3), Harga Wortel (X2), Harga Pupuk
(X1)
b. Dependent Variable: Dosis Pupuk Y
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 35834.330 3 11944.777 122.064 .000a
Residual 1272.141 13 97.857
Total 37106.471 16
a. Predictors: (Constant), Pengalaman Bertani (X3), Harga Wortel (X2), Harga Pupuk (X1)
b. Dependent Variable: Dosis Pupuk (Y)
Harga Wortel (X2) -.003 .003 -.060 -1.140 .275 -.266 -.302 -.059
Pengalaman
Bertani (X3) -.489 .339 -.075 -1.443 .173 .055 -.371 -.074
a. Dependent Variable: Dosis Pupuk
(Y)
Lampiran 10. Hasil Analisis One Sample T-Test Kubis
One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
Dosis Pupuk Petani 20 6.0825E2 80.87149 18.08341
One-Sample Test
Test Value = 0
t df Sig. (2-tailed) Mean Difference
95% Confidence Interval of
the Difference
Lower Upper
Dosis Pupuk Petani 33.636 19 .000 608.25000 570.4010 646.0990
Lampiran 11. Hasil Analisis One Sample T-Test Kubis Bunga
One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
Dosis Pupuk Petani 43 6.6372E2 139.99614 21.34921
One-Sample Test
Test Value = 0
t df Sig. (2-tailed) Mean Difference
95% Confidence Interval of the
Difference
Lower Upper
Dosis Pupuk
Lampiran 12. Hasil Analisis One Sample T-Test Wortel
One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
Dosis Pupuk Petani 17 1.9391E2 48.13952 11.67555
One-Sample Test
Test Value = 0
t df Sig. (2-tailed) Mean Difference
95% Confidence Interval of the
Difference
Lower Upper
