Lampiran 1. Karakteristik Petani Kubis Bunga Kecamatan Tigapanah Kabupaten Karo 2015
Responden Nama
Pengalaman Bertani
( Tahun) Usia Pendidikan
Jumlah Tanggungan
1 Diamon Pelawi 20 42 SMA 5
2 Tommi 20 45 SMP 4
3 Robin 9 40 SMA 3
4 Andarias Sinuhaji 20 50 SMA 3
5 Indra Tarigan 3 25 SMP 1
6 Ulina Br Sinuhaji 25 40 SMA 5
7 Demo Depari 30 46 SMA 4
8 Mama Petro 35 49 SD 4
9 Gindo Ginting 15 29 SMP 0
10 Sariwangi 25 43 SMA 8
11 Hendra Sembiring 8 38 SMA 2
12 Diamon Bukit 6 27 SMP 2
13 Irawati Br Ginting 8 29 SMA 3
14 Endia Pandia 12 33 SMA 2
15 Sarjani Sembiring 4 30 SMP 3
16
Mamak Margareta
Pandia 20 52 SD 4
17 Edi Syahputra Sembiring 4 34 SMA 1
18 Armut Br Ginting 14 46 S1 1
19 Rela Ginting 36 56 SMA 2
20 Eko Diska Barus 4 26 SMA 1
21 Junanda Purba 7 37 S1 2
22 Nurboti Br Ginting 5 39 SMP 3
23 Ridwan Parangin-angin 12 40 SMP 3
24 Fitri Br Barus 8 30 SMA 1
25 Reksa Ginting 5 66 SMA 4
26 Jasmin Kemit 10 50 SMA 4
27 Lela Br Purba 2 35 SMA 3
28 Dolat J. Ginting 11 41 S1 2
29 Lekson Br Tarigan 4 59 SD 3
30 Ratna Br Tarigan 4 33 SMA 1
31 Ahmadi Sukapiring 5 48 SMA 2
32 Rolianta Br Sinuhaji 7 42 STM 1
33 Andi Ginting 10 35 SMA 3
34 Dafit Sinuhaji 15 39 SMA 4
35 Auri 5 25 SD 3
36 Lesna Sembiring 15 36 SMP 5
37 Supardi Pandia 13 39 SMA 6
38 Heuvaruati Purba 10 32 SMA 6
39 Eka Susanti 3 25 SMA 2
40 M. Sulaiman Lubis 3 26 STM 2
41 Hanni Sembiring 7 33 STM 3
42 Muklis 2 26 SMP 1
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
0.92874175E+01-0.90470059E-01 0.48266578E-01 0.25704662E-03 iteration = 45 func evals = 882 llf = 0.41558471E+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 :
firm eff.-est. 1 0.99836971E+00 2 0.99838072E+00 3 0.99838072E+00 4 0.99837104E+00 5 0.99838367E+00
6 0.99838367E+00 7 0.99837377E+00 8 0.99837138E+00 9 0.99838400E+00 10 0.99838876E+00 11 0.99836870E+00 12 0.99838886E+00 13 0.99838886E+00 14 0.99837167E+00 15 0.99838429E+00 16 0.99837420E+00 17 0.99838162E+00 18 0.99836918E+00 19 0.99837194E+00 20 0.99838456E+00 21 0.99838456E+00 22 0.99838460E+00 23 0.99838472E+00 24 0.99837219E+00 25 0.99837219E+00 26 0.99837219E+00 27 0.99837700E+00 28 0.99838480E+00 29 0.99838956E+00 30 0.99838492E+00 31 0.99837242E+00 32 0.99837242E+00 33 0.99837242E+00 34 0.99838503E+00 35 0.99838503E+00 36 0.99838503E+00 37 0.99837249E+00 38 0.99838986E+00 39 0.99837252E+00 40 0.99838523E+00 41 0.99837263E+00 42 0.99837282E+00 43 0.99837300E+00 mean efficiency = 0.99837881E+00
Lampiran 3. Karakteristik Petani Kubis Kecamatan Tigapanah Kabupaten Karo Tahun 2015
Responden Nama
Pengalaman Bertani
( Tahun) Usia Pendidikan
Jumlah Tanggungan
1 Diamon Pelawi 20 42 SMA 5
2 Demo Depari 25 46 SMA 4
3 Ulina Br Sinuhaji 25 40 SMA 5
4 Supardi Pandia 13 39 SMA 6
5 Andarias Sinuhaji 20 50 SMA 3
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 :
firm eff.-est. 1 0.99964373E+00 2 0.99964379E+00 3 0.99964494E+00 4 0.99964429E+00 5 0.99964361E+00 6 0.99964361E+00 7 0.99964359E+00 8 0.99964361E+00 9 0.99964379E+00 10 0.99964379E+00 11 0.99964349E+00 12 0.99964449E+00 13 0.99964389E+00 14 0.99964372E+00 15 0.99964407E+00 16 0.99964407E+00 17 0.99964449E+00 18 0.99964354E+00 19 0.99964378E+00 20 0.99964375E+00 mean efficiency = 0.99964390E+00
Lampiran 5. Karakteristik Petani Wortel Kecamatan Tigapanah Kabupaten Karo Tahun 2015
Responden Nama
Pengalaman Bertani
( Tahun) Usia Pendidikan
Jumlah Tanggungan
1 Tommi 20 45 SMP 4
2 Demo Depari 25 46 SMA 4
3 Diamon Bukit 6 27 SMP 2
4 Ahmadi Sukapiring 5 48 SMA 2
5 Andarias Sinuhaji 20 50 SMA 3
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 mu is restricted to be zero eta is restricted to be zero
iteration = 0 func evals = 20 llf = 0.58245533E+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 Change
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 Variables Entered Variables Removed Method 1 Pengalaman Bertani (X3), Harga Wortel (X2), Harga Pupuk (X1)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 .983a .966 .958 9.89227 .966 122.064 3 13 .000
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)
Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. Correlations
B Std. Error Beta Zero-order Partial Part
1 (Constant) 9.440 13.810 .684 .506
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
