Analisis Efisiensi Penggunaan Pupuk Oleh Petani Pada Tanaman Sayuran (Kubis, Kubis Bunga, Dan Wortel)(Studi Kasus : Kecamatan Tigapanah, Kabupaten Karo)

  L A M P I R A N Lampiran 1. Karakteristik Petani Kubis Bunga Kecamatan Tigapanah Kabupaten Karo 2015

  Responden Nama Pengalaman Bertani

  4

  41 S1

  2

  29 Lekson Br Tarigan

  4

  59 SD

  3

  30 Ratna Br Tarigan

  33 SMA

  28 Dolat J. Ginting

  1

  31 Ahmadi Sukapiring

  5

  48 SMA

  2

  32 Rolianta Br Sinuhaji

  7

  42 STM

  11

  3

  33 Andi Ginting

  25 Reksa Ginting

  23 Ridwan Parangin-angin

  12

  40 SMP

  3

  24 Fitri Br Barus

  8

  30 SMA

  1

  5

  35 SMA

  66 SMA

  4

  26 Jasmin Kemit

  10

  50 SMA

  4

  27 Lela Br Purba

  2

  1

  10

  39 SMP

  7

  3

  25 SMA

  2

  40 M. Sulaiman Lubis

  3

  26 STM

  2

  41 Hanni Sembiring

  33 STM

  6

  3

  42 Muklis

  2

  26 SMP

  1

  43 B. Tarigan

  7

  34 SMP

  39 Eka Susanti

  32 SMA

  35 SMA

  3

  3

  34 Dafit Sinuhaji

  15

  39 SMA

  4

  35 Auri

  5

  25 SD

  36 Lesna Sembiring

  10

  15

  36 SMP

  5

  37 Supardi Pandia

  13

  39 SMA

  6

  38 Heuvaruati Purba

  3

  5

  ( Tahun) Usia Pendidikan Jumlah

  35

  25

  40 SMA

  5

  7 Demo Depari

  30

  46 SMA

  4

  8 Mama Petro

  49 SD

  1

  4

  9 Gindo Ginting

  15

  29 SMP

  10 Sariwangi

  25

  43 SMA

  8

  6 Ulina Br Sinuhaji

  25 SMP

  8

  4

  Tanggungan

  1 Diamon Pelawi

  20

  42 SMA

  5

  2 Tommi

  20

  45 SMP

  3 Robin

  3

  9

  40 SMA

  3

  4 Andarias Sinuhaji

  20

  50 SMA

  3

  5 Indra Tarigan

  11 Hendra Sembiring

  38 SMA

  22 Nurboti Br Ginting

  56 SMA

  34 SMA

  1

  18 Armut Br Ginting

  14

  46 S1

  1

  19 Rela Ginting

  36

  2

  17 Edi Syahputra Sembiring

  20 Eko Diska Barus

  4

  26 SMA

  1

  21 Junanda Purba

  7

  37 S1

  2

  4

  4

  2

  14 Endia Pandia

  12 Diamon Bukit

  6

  27 SMP

  2

  13 Irawati Br Ginting

  8

  29 SMA

  3

  12

  52 SD

  33 SMA

  2

  15 Sarjani Sembiring

  4

  30 SMP

  3

  16 Mamak Margareta Pandia

  20

  3 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

  Pengalaman Bertani Jumlah Responden Nama ( Tahun) Usia Pendidikan 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

  6 Indra Tarigan

  3

  25 SMP

  1 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

  46 SMA

  2

  15 Tommi

  20

  45 SMP

  4

  16 Rela Ginting

  36

  56 SMA

  2

  17 Armut Br Ginting

  14

  1

  6

  18 Margareta Pandia

  20

  52 SD

  4

  19 B. Tarigan

  7

  34 SMP

  3

  20 Robin

  9

  40 SMA

  27 SMP

  14 Diamon Bukit

  35

  5

  49 SD

  4

  8 Hendra Sembiring

  8

  38 SMA

  2

  9 Rolianta Br Sinuhaji

  7

  42 STM

  1

  10 Ahmadi Sukapiring

  48 SMA

  3

  2

  11 Lekson Br Tarigan

  4

  59 SD

  3

  12 Dolat J. Ginting

  11

  41 S1

  2

  13 Sarjani Sembiring

  4

  30 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 number of time periods = 1 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

  Pengalaman Bertani Jumlah

  Responden Nama ( Tahun) Usia Pendidikan 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

  6 Diamon Pelawi

  20

  42 SMA

  5

  

Lampiran 6. Hasil Analisis Efisiensi Teknis Penggunaan Pupuk pada Wortel

  6

  3

  13 Ridwan Parangin-Angin

  12

  40 SMP

  3

  14 Supardi Pandia

  13

  39 SMA

  15 Rolianta Br Sinuhaji

  8

  7

  42 STM

  1

  16 Edi Syahputra Sembiring

  4

  34 SMA

  1

  17 Bersih Sembiring

  20

  29 SMA

  12 Irawati Br Ginting

  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 :

  9 Hendra Sembiring

  7 Robin

  9

  40 SMA

  3

  8 Fitri Br Barus

  8

  30 SMA

  1

  8

  5

  38 SMA

  2

  10 Reksa Ginting

  5

  66 SMA

  4

  11 Ulina Br Sinuhaji

  25

  40 SMA

  65 SMP 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 [note that this statistic has a mixed chi-square distribution]

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 mean efficiency = 0.99926888E+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 b

  43 Variables Entered/Removed Variables Variables Model Entered Removed Method

  1 Pengalaman Bertani (X3), Harga Pupuk . Enter (X1), Harga Kubis Bunga a (X2)

a. All requested variables entered.

  b. Dependent Variable: Dosis Pupuk (Y) b Model Summary

  Change Statistics Adjusted R Std. Error of the Sig. F

Model R R Square Square Estimate R Square Change F Change df1 df2 Change

  1 .732 a .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 ANOVA

b

Model Sum of Squares df Mean Square F Sig.

  1 Regression 440944.035 3 146981.345 14.998 .000 a 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) Coefficients a

  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

  a. Dependent Variable: Dosis Pupuk (Y)

  Descriptive Statistics

  Lampiran 8. Hasil

  Mean Std. Deviation N

  Analisis Statistik Kubis

  Dosis Pupuk (Y) 6.0825E2 80.87149

  20 Harga Pupuk (X1) 3.8888E6 7.35078E5

  20 Harga Kubis (X2) 1.0400E3 354.51969

  20 Pengalaman Bertani (X3) 14.6000 10.10159

  20 b Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  1 Pengalaman Bertani (X3), Harga Pupuk . Enter (X1), Harga a Kubis (X2)

a. All requested variables entered.

  b. Dependent Variable: Dosis Pupuk (Y) b Model Summary

  Change Statistics Adjusted R Std. Error of the

Model R R Square Square Estimate R Square Change F Change df1 df2 Sig. F Change

a 1 .596 .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)

  b ANOVA Model Sum of Squares df Mean Square F Sig. a

  1 Regression 44155.028 3 14718.343 2.940 .065 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) a

Coefficients

  Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta t Sig.

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 b

  17 Variables Entered/Removed 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 Summary b

  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 .983 a .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

  ANOVA b Model Sum of Squares df Mean Square F Sig.

  1 Regression 35834.330 3 11944.777 122.064 .000 a 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)

Coefficients

a

  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 Pupuk (X1) .000 .000 .975 18.386 .000 .978 .981 .944

  

Harga Wortel (X2) -.003 .003 -.060 -1.140 .275 -.266 -.302 -.059

Pengalaman

  • .489 .339 -.075 -1.443 .173 .055 -.371 -.074 Bertani (X3)

  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 95% Confidence Interval of the Difference t df Sig. (2-tailed) Mean 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 95% Confidence Interval of the Difference t df Sig. (2-tailed) Mean Difference Lower Upper

  Dosis Pupuk 31.089 42 .000 663.72093 620.6365 706.8054 Petani 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 95% Confidence Interval of the Difference t df Sig. (2-tailed) Mean Difference Lower Upper

  Dosis Pupuk Petani 16.608 16 .000 193.91176 169.1607 218.6628

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