DAFTAR PUSTAKA
“TERIMA KASIH ATAS BANTUAN DAN KERJASAMA ANDA UNTUK BERSEDIA MENGISI KUESIONER INI”
Lampiran 2 Uji Validitas dan Reliabilitas untuk Analisis Sikap terhadap Atribut Benih Unggul Jagung
Tingkat Kepentingan Petani terhadap Atribut Benih Jagung
Scale: ALL VARIABLES
Case Processing Summary
N %
Cases Valid 40 100.0 Excludeda 0 .0
Total 40 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .845 .848 17
Lampiran 2 (lanjutan) Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted Prdktvts 22.58 17.020 .416 .842 Tahan H/P 22.88 15.394 .529 .832 Umur 23.00 15.231 .535 .832 DK 22.95 15.177 .560 .831 Efsnsi_guna_pupuk 22.80 16.113 .364 .841 Dy_smpn 23.30 16.113 .364 .841 Kmsn 23.38 15.984 .393 .839 Jns/Var 22.85 15.362 .553 .831 Uk_bnh 23.03 15.410 .484 .835 Tgl_kadlwrs 23.35 16.336 .332 .842 Uk_tgkl_hsl_pnn 22.90 15.015 .625 .827 Lbl_benih 23.43 15.943 .386 .840 P_bnh 22.95 15.792 .393 .840 Aks_bnh 23.18 15.994 .345 .842 Stk_bnh 23.23 16.025 .352 .842 Dmplt_lap 23.45 15.177 .497 .834 Ped/Juk/Leaf/Bros 23.58 15.328 .628 .828
Lampiran 2 (lanjutan)
Tingkat Kepercayaan Petani terhadap Atribut Benih Jagung Komposit
Reliability
Scale: ALL VARIABLES
Case Processing Summary
N %
Cases Valid 40 100.0 Excludeda 0 .0
Total 40 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .880 .889 17
Lampiran 2 (lanjutan) Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted Prdktvts 15.88 21.804 .578 .870 Tahan H/P 15.50 21.846 .447 .877 Umur 16.15 22.336 .475 .875 DK 15.90 23.118 .441 .876 Efsnsi_guna_pupuk 15.70 20.985 .568 .871 Dy_smpn 16.05 22.972 .637 .872 Kmsn 16.03 23.204 .640 .873 Jns/Var 15.88 22.266 .631 .870 Uk_bnh 16.20 21.292 .604 .869 Tgl_kadlwrs 15.95 21.997 .503 .874 Uk_tgkl_hsl_pnn 15.95 22.408 .538 .872 Lbl_benih 16.05 21.279 .555 .872 P_bnh 16.23 21.563 .593 .870 Aks_bnh 15.90 23.323 .385 .877 Stk_bnh 15.88 23.138 .401 .877 Dmplt_lap 15.88 22.984 .441 .876 Ped/Juk/Leaf/Bros 16.10 21.579 .558 .871
Lampiran 2 (lanjutan)
Tingkat Kepercayaan Petani terhadap Atribut Benih Jagung Hibrida
Reliability
Scale: ALL VARIABLES
Case Processing Summary
N %
Cases Valid 40 100.0
Excludeda 0 .0 Total 40 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .922 .920 17
Lampiran 2 (lanjutan) Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted Prdktvts 10.97 71.358 .724 .914 Tahan H/P 12.70 76.421 .386 .922 Umur 12.52 77.128 .348 .923 DK 11.22 75.256 .500 .919 Efsnsi_guna_pupuk 11.20 72.369 .655 .915 Dy_smpn 11.37 72.702 .629 .916 Kmsn 11.37 72.702 .629 .916 Jns/Var 11.20 70.831 .772 .912 Uk_bnh 11.22 72.025 .696 .914 Tgl_kadlwrs 11.25 73.885 .596 .917 Uk_tgkl_hsl_pnn 11.20 70.831 .772 .912 Lbl_benih 11.37 72.702 .629 .916 P_bnh 11.15 71.464 .759 .913 Aks_bnh 11.37 72.702 .629 .916 Stk_bnh 11.20 70.831 .772 .912 Dmplt_lap 12.10 76.041 .433 .921 Ped/Juk/Leaf/Bros 12.15 76.695 .424 .921
Lampiran 2 (lanjutan)
Tingkat Kepercayaan Petani terhadap Atribut Benih Jagung Lokal
Reliability
Scale: ALL VARIABLES
Case Processing Summary
N %
Cases Valid 40 100.0
Excludeda 0 .0 Total 40 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .957 .956 17
Lampiran 2 (lanjutan) Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted Prdktvts -5.95 73.792 .798 .954 Tahan H/P -6.63 78.702 .444 .959 Umur -6.55 79.331 .466 .959 DK -6.55 79.331 .466 .959 Efsnsi_guna_pupuk -6.38 77.369 .542 .958 Dy_smpn -6.38 67.163 .888 .953 Kmsn -6.13 70.676 .866 .952 Jns/Var -6.20 68.933 .867 .953 Uk_bnh -6.08 75.097 .761 .955 Tgl_kadlwrs -6.15 68.644 .952 .951 Uk_tgkl_hsl_pnn -6.15 72.131 .830 .953 Lbl_benih -6.05 69.895 .892 .952 P_bnh -6.28 72.769 .718 .955 Aks_bnh -6.23 75.410 .556 .958 Stk_bnh -5.90 74.297 .768 .955 Dmplt_lap -6.03 73.717 .786 .954 Ped/Juk/Leaf/Bros -6.00 71.538 .889 .952
Lampiran 3 Uji Validitas dan Reliabilitas untuk Analisis Hubungan Kepuasan dan Loyalitas Petani terhadap Penggunaan Jagung Komposit
Frequency Table
X11
Frequency Percent Valid Percent Cumulative Percent
Valid 4.00 95 79.2 79.2 79.2
5.00 25 20.8 20.8 100.0
Total 120 100.0 100.0
X12
Frequency Percent Valid Percent Cumulative Percent
Valid 4.00 29 24.2 24.2 24.2
5.00 91 75.8 75.8 100.0
Total 120 100.0 100.0
X13
Frequency Percent Valid Percent Cumulative Percent
Valid 3.00 1 .8 .8 .8
4.00 76 63.3 63.3 64.2
5.00 43 35.8 35.8 100.0
Lampiran 3 (lanjutan)
X14
Frequency Percent Valid Percent Cumulative Percent
Valid 4.00 74 61.7 61.7 61.7
5.00 46 38.3 38.3 100.0
Total 120 100.0 100.0
X15
Frequency Percent Valid Percent Cumulative Percent
Valid 4.00 79 65.8 65.8 65.8
5.00 41 34.2 34.2 100.0
Total 120 100.0 100.0
X16
Frequency Percent Valid Percent Cumulative Percent
Valid 4.00 98 81.7 81.7 81.7
5.00 22 18.3 18.3 100.0
Total 120 100.0 100.0
X17
Frequency Percent Valid Percent Cumulative Percent
Valid 3.00 1 .8 .8 .8
4.00 105 87.5 87.5 88.3
5.00 14 11.7 11.7 100.0
Lampiran 3 (lanjutan)
X18
Frequency Percent Valid Percent Cumulative Percent Valid 3.00 1 .8 .8 .8 4.00 102 85.0 85.0 85.8 5.00 17 14.2 14.2 100.0 Total 120 100.0 100.0 X19
Frequency Percent Valid Percent Cumulative Percent
Valid 4.00 90 75.0 75.0 75.0
5.00 30 25.0 25.0 100.0
Total 120 100.0 100.0
X110
Frequency Percent Valid Percent Cumulative Percent
Valid 4.00 26 21.7 21.7 21.7
5.00 94 78.3 78.3 100.0
Total 120 100.0 100.0
X21
Frequency Percent Valid Percent Cumulative Percent
Valid 4.00 83 69.2 69.2 69.2
5.00 37 30.8 30.8 100.0
Lampiran 3 (lanjutan)
X22
Frequency Percent Valid Percent Cumulative Percent Valid 3.00 2 1.7 1.7 1.7 4.00 93 77.5 77.5 79.2 5.00 25 20.8 20.8 100.0 Total 120 100.0 100.0 X31
Frequency Percent Valid Percent Cumulative Percent
Valid 4.00 98 81.7 81.7 81.7
5.00 22 18.3 18.3 100.0
Total 120 100.0 100.0
X32
Frequency Percent Valid Percent Cumulative Percent
Valid 2.00 1 .8 .8 .8
4.00 98 81.7 81.7 82.5
5.00 21 17.5 17.5 100.0
Lampiran 3 (lanjutan)
X41
Frequency Percent Valid Percent Cumulative Percent Valid 3.00 4 3.3 3.3 3.3 4.00 109 90.8 90.8 94.2 5.00 7 5.8 5.8 100.0 Total 120 100.0 100.0 X42
Frequency Percent Valid Percent Cumulative Percent Valid 3.00 4 3.3 3.3 3.3 4.00 109 90.8 90.8 94.2 5.00 7 5.8 5.8 100.0 Total 120 100.0 100.0 Y1
Frequency Percent Valid Percent Cumulative Percent
Valid 4.00 111 92.5 92.5 92.5
5.00 9 7.5 7.5 100.0
Total 120 100.0 100.0
Y2
Frequency Percent Valid Percent
Cumulative Percent
Valid 4.00 79 65.8 65.8 65.8
5.00 41 34.2 34.2 100.0
Lampiran 3 (lanjutan)
Y3
Frequency Percent Valid Percent
Cumulative Percent Valid 3.00 2 1.7 1.7 1.7 4.00 111 92.5 92.5 94.2 5.00 7 5.8 5.8 100.0 Total 120 100.0 100.0 Y4
Frequency Percent Valid Percent
Cumulative Percent
Valid 4.00 78 65.0 65.0 65.0
5.00 42 35.0 35.0 100.0
Lampiran 4 Lisrel Software Information
DATE: 8/27/2012 TIME: 15:55
L I S R E L 8.30
BY
Karl G. Jöreskog & Dag Sörbom
This program is published exclusively by Scientific Software International, Inc.
7383 N. Lincoln Avenue, Suite 100 Chicago, IL 60646-1704, U.S.A.
Phone: (800)247-6113, (847)675-0720, Fax: (847)675-2140 Copyright by Scientific Software International, Inc., 1981-99
Use of this program is subject to the terms specified in the Universal Copyright Convention.
Website: www.ssicentral.com
Lampiran 5 Sintaks Program Simplis yang Membentuk Path Diagram Model Penelitian
Analisis Hubungan kepuasan dan loyalitas petani terhadap penggunaan benih unggul jagung komposit
Observed Variables
X11 X12 X13 X14 X15 X16 X17 X18 X19 X110 X21 X22 X31 X32 X41 X42 Y1 Y2 Y3
Y4
Correlation Matrix From File D:\SEMASRUL\DATA1.COR Sample Size = 120
Latent Variables PRODUK HARGA TEMPAT PROMOSI KEPUASAN LOYALITAS Relationships X11 X12 X13 X14 X15 X16 X17 X18 X19 X110 = PRODUK X21 X22 = HARGA X31 X32 = TEMPAT X41 X42 = PROMOSI Y1 = KEPUASAN Y2 Y3 Y4 = LOYALITAS
KEPUASAN = PRODUK HARGA TEMPAT PROMOSI LOYALITAS = KEPUASAN
Path Diagram
OPTIONS RO RC=1 ME=UL AD=OFF IT=300
SET THE ERROR VARIANCE OF Y1 EQUAL TO FREE SET THE ERROR VARIANCE OF X42 EQUAL TO FREE SET THE ERROR VARIANCE OF X21 EQUAL TO FREE SET THE ERROR VARIANCE OF Y2 EQUAL TO FREE SET THE ERROR VARIANCE OF HARGA EQUAL TO FREE !SET THE ERROR VARIANCE OF LOYALITAS EQUAL TO 0.05
set the correlation between KEPUASAN and LOYALITAS equal to -0.95
!set the error covariance between KEPUASAN and LOYALITAS to free set the error covariance between X13 and X12 to free
set the error covariance between X14 and X13 to free set the error covariance between X15 and X12 to free set the error covariance between X15 and X13 to free set the error covariance between X15 and X14 to free set the error covariance between X41 and Y4 to free set the error covariance between X42 and X11 to free set the error covariance between X11 and Y1 to free set the error covariance between X11 and Y3 to free set the error covariance between X11 and Y4 to free set the error covariance between X12 and Y2 to free set the error covariance between X13 and Y2 to free set the error covariance between X14 and Y2 to free set the error covariance between X14 and X11 to free set the error covariance between X14 and X12 to free set the error covariance between X15 and Y2 to free set the error covariance between X16 and Y1 to free set the error covariance between X17 and Y2 to free set the error covariance between X17 and Y3 to free set the error covariance between X17 and Y4 to free set the error covariance between X18 and Y1 to free set the error covariance between X18 and Y3 to free set the error covariance between X19 and Y4 to free set the error covariance between X19 and X12 to free set the error covariance between X19 and X13 to free set the error covariance between X19 and X18 to free set the error covariance between X110 and X19 to free
Lampiran 5 (lanjutan)
set the error covariance between X21 and Y2 to free set the error covariance between X21 and Y3 to free set the error covariance between X21 and X11 to free set the error covariance between X21 and X12 to free set the error covariance between X21 and X17 to free set the error covariance between X22 and Y1 to free set the error covariance between X22 and X16 to free set the error covariance between X22 and X18 to free set the error covariance between X31 and Y2 to free set the error covariance between X31 and X11 to free set the error covariance between X31 and X12 to free set the error covariance between X31 and X14 to free set the error covariance between X31 and X16 to free set the error covariance between X31 and X19 to free set the error covariance between X32 and X11 to free set the error covariance between X32 and X14 to free set the error covariance between X32 and X17 to free set the error covariance between X32 and X19 to free set the error covariance between X32 and X110 to free set the error covariance between X41 and X11 to free set the error covariance between X41 and X12 to free set the error covariance between X41 and X14 to free set the error covariance between X41 and X16 to free set the error covariance between X41 and X19 to free set the error covariance between X41 and X110 to free set the error covariance between X41 and X21 to free set the error covariance between X41 and X22 to free set the error covariance between X42 and Y2 to free set the error covariance between X42 and Y3 to free set the error covariance between X42 and X12 to free set the error covariance between X42 and X15 to free set the error covariance between X42 and X22 to free !set the error covariance between Y2 and Y1 to free set the error covariance between X11 and Y2 to free set the error covariance between X13 and Y4 to free set the error covariance between X14 and Y1 to free set the error covariance between X16 and Y2 to free set the error covariance between X18 and Y2 to free set the error covariance between X18 and X16 to free set the error covariance between X110 and Y2 to free set the error covariance between X21 and X21 to free !set the error covariance between X22 and X21 to free !set the error covariance between X42 and X32 to free End of Problem
Lampiran 6 Matriks Kovarian dan Koefisien Model
Sample Size = 120
Covariance Matrix to be Analyzed
Y1 Y2 Y3 Y4 X11 X12 --- --- --- --- --- --- Y1 2.00 Y2 -0.39 2.00 Y3 0.22 0.16 2.00 Y4 -0.19 0.22 -0.11 2.00 X11 0.73 -0.21 0.35 -0.40 2.00 X12 -0.15 0.38 0.21 0.23 -0.09 2.00 X13 -0.33 0.43 0.05 0.26 -0.29 0.58 X14 -0.44 0.36 0.13 0.17 0.11 0.44 X15 0.14 0.18 0.20 0.16 0.26 0.38 X16 0.54 -0.22 0.03 -0.06 0.33 -0.25 X17 0.69 -0.55 -0.15 -0.41 0.49 -0.52 X18 0.63 -0.35 -0.16 -0.16 0.63 -0.41 X19 0.43 0.12 -0.03 0.37 0.46 0.11 X110 -0.35 0.32 -0.18 0.25 -0.32 0.23 X21 0.34 0.21 0.37 0.13 0.47 0.23 X22 0.50 0.00 -0.16 0.06 0.22 -0.05 X31 0.26 0.36 0.22 -0.06 0.41 0.38 X32 0.28 -0.01 0.01 -0.10 0.52 0.10 X41 -0.08 -0.01 -0.04 0.50 -0.49 -0.34 X42 -0.08 -0.24 -0.33 0.01 -0.98 -0.34
Covariance Matrix to be Analyzed
X13 X14 X15 X16 X17 X18 --- --- --- --- --- --- X13 2.00 X14 0.73 2.00 X15 0.66 0.81 2.00 X16 -0.05 -0.04 0.50 2.00 X17 -0.34 -0.32 0.36 1.00 2.00 X18 -0.21 -0.30 0.40 0.90 0.98 2.00 X19 0.23 0.03 0.32 0.39 0.41 0.63 X110 0.31 0.15 0.07 -0.22 -0.16 -0.07 X21 0.10 0.11 0.21 0.27 -0.13 -0.02 X22 0.16 -0.07 0.16 0.34 0.23 0.33 X31 0.18 0.43 0.04 0.31 -0.22 -0.14 X32 0.16 0.26 0.02 0.09 -0.31 -0.12 X41 0.12 -0.25 -0.12 0.19 -0.06 0.08 X42 0.01 -0.13 -0.56 -0.09 -0.28 -0.27
Lampiran 6 (lanjutan)
Covariance Matrix to be Analyzed
X19 X110 X21 X22 X31 X32 --- --- --- --- --- --- X19 2.00 X110 0.24 2.00 X21 0.13 -0.08 2.00 X22 0.21 0.08 0.58 2.00 X31 0.39 0.20 0.74 0.28 2.00 X32 0.27 0.38 0.72 0.39 0.90 2.00 X41 0.46 0.45 -0.50 0.20 -0.24 -0.10 X42 0.05 0.24 -0.50 0.20 -0.08 0.15
Covariance Matrix to be Analyzed X41 X42 --- --- X41 2.00 X42 0.85 2.00 Number of Iterations = 45
LISREL Estimates (unweighted Least Square) Y1 = 1.00*KEPUASAN,, R² = 1.00 (0.15) 9.66 Y2 = 1.00*LOYALITA,, R² = 1.00 (0.12) 12.23 Y3 = 0.05*LOYALITA, Errorvar.= 1.99 , R² = 0.25 (0.045) (0.094) 1.59 21.28 Y4 = 0.11*LOYALITA, Errorvar.= 1.98 , R² = 0.11 (0.044) (0.11) 3.37 17.24 X11 = 0.41*PRODUK, Errorvar.= 1.67 , R² = 0.16 (0.049) (0.13) 11.71 13.17 X12 = - 0.27*PRODUK, Errorvar.= 1.85 , R² = 0.73 (0.048) (0.094) -7.95 19.65 X13 = - 0.21*PRODUK, Errorvar.= 1.91 , R² = 0.44 (0.048) (0.096) -6.21 19.94 X14 = - 0.14*PRODUK, Errorvar.= 1.96 , R² = 0.21 (0.050) (0.095) -4.06 20.52
Lampiran 6 (lanjutan) X15 = 0.30*PRODUK, Errorvar.= 1.82 , R² = 0.88 (0.046) (0.10) 9.08 18.11 X16 = 0.57*PRODUK, Errorvar.= 1.34 , R² = 0.33 (0.057) (0.12) 14.12 11.34 X17 = 0.75*PRODUK, Errorvar.= 0.88 , R² = 0.56 (0.062) (0.18) 16.98 4.87 X18 = 0.68*PRODUK, Errorvar.= 1.15 , R² = 0.42 (0.065) (0.14) 14.14 7.95 X19 = 0.36*PRODUK, Errorvar.= 1.74 , R² = 0.13 (0.052) (0.11) 9.94 16.20 X110 = - 0.19*PRODUK, Errorvar.= 1.93 , R² = 0.37 (0.046) (0.093) -5.92 20.77 X21 = 0.68*HARGA, Errorvar.= 2.00 , R² = 0.67 (0.078) (0.092) 12.28 21.82 X22 = 0.35*HARGA, Errorvar.= 2.00 , R² = 0.73 (0.076) (0.092) 6.53 21.82 X31 = 0.68*TEMPAT, Errorvar.= 1.07 , R² = 0.47 (0.086) (0.20) 11.20 5.34 X32 = 0.66*TEMPAT, Errorvar.= 1.12 , R² = 0.44 (0.077) (0.16) 12.14 6.86 X41 = 0.42*PROMOSI, Errorvar.= 1.65 , R² = 0.18 (0.067) (0.15) 8.92 11.24 X42 = 1.00*PROMOSI,, R² = 1.00 (0.046) 30.99
Error Covariance for X11 and Y1 = 0.35 (0.097) 3.57 Error Covariance for X11 and Y2 = -0.31 (0.091) -3.41
Lampiran 6 (lanjutan)
Error Covariance for X11 and Y3 = 0.34 (0.092) 3.73 Error Covariance for X11 and Y4 = -0.41 (0.091) -4.46 Error Covariance for X12 and Y2 = 0.44 (0.092) 4.81 Error Covariance for X13 and Y2 = 0.48 (0.092) 5.19 Error Covariance for X13 and Y4 = 0.27 (0.092) 2.91 Error Covariance for X13 and X12 = 0.47 (0.093) 5.05 Error Covariance for X14 and Y1 = -0.30 (0.094) -3.17 Error Covariance for X14 and Y2 = 0.40 (0.092) 4.30 Error Covariance for X14 and X11 = 0.22 (0.094) 2.38
Lampiran 6 (lanjutan)
Error Covariance for X14 and X12 = 0.37 (0.092) 3.97
Error Covariance for X14 and X13 = 0.67 (0.092) 7.33 Error Covariance for X15 and Y2 = 0.11 (0.092) 1.15 Error Covariance for X15 and X12 = 0.54 (0.092) 5.80 Error Covariance for X15 and X13 = 0.79 (0.092) 8.51 Error Covariance for X15 and X14 = 0.89 (0.092) 9.68 Error Covariance for X16 and Y1 = 0.00095 (0.11) 0.0088 Error Covariance for X16 and Y2 = -0.37 (0.095) -3.92 Error Covariance for X17 and Y2 = -0.74 (0.096) -7.69
Lampiran 6 (lanjutan)
Error Covariance for X17 and Y3 = -0.16 (0.092) -1.72 Error Covariance for X17 and Y4 = -0.43 (0.092) -4.68 Error Covariance for X18 and Y1 = 0.014 (0.12) 0.12 Error Covariance for X18 and Y2 = -0.51 (0.096) -5.37 Error Covariance for X18 and Y3 = -0.17 (0.092) -1.85 Error Covariance for X18 and X16 = 0.16 (0.12) 1.36 Error Covariance for X19 and Y4 = 0.36 (0.092) 3.89 Error Covariance for X19 and X12 = 0.30 (0.094) 3.25 Error Covariance for X19 and X13 = 0.38 (0.093) 4.13
Lampiran 6 (lanjutan)
Error Covariance for X19 and X18 = 0.15 (0.10) 1.50 Error Covariance for X110 and Y2 = 0.36 (0.092) 3.97 Error Covariance for X110 and X19 = 0.38 (0.092) 4.13 Error Covariance for X21 and Y2 = 0.12 (0.093) 1.31 Error Covariance for X21 and Y3 = 0.37 (0.092) 4.02 Error Covariance for X21 and X11 = 0.34 (0.094) 3.62 Error Covariance for X21 and X12 = 0.31 (0.093) 3.39 Error Covariance for X21 and X17 = -0.36 (0.10) -3.51 Error Covariance for X22 and Y1 = 0.32 (0.093) 3.48
Lampiran 6 (lanjutan)
Error Covariance for X22 and X16 = 0.25 (0.093) 2.72 Error Covariance for X22 and X18 = 0.23 (0.093) 2.48 Error Covariance for X31 and Y2 = 0.29 (0.091) 3.14 Error Covariance for X31 and X11 = 0.49 (0.092) 5.37 Error Covariance for X31 and X12 = 0.33 (0.092) 3.60 Error Covariance for X31 and X14 = 0.40 (0.092) 4.37 Error Covariance for X31 and X16 = 0.42 (0.092) 4.58 Error Covariance for X31 and X19 = 0.46 (0.092) 5.04 Error Covariance for X32 and X11 = 0.59 (0.092) 6.49
Lampiran 6 (lanjutan)
Error Covariance for X32 and X14 = 0.23 (0.092) 2.55 Error Covariance for X32 and X17 = -0.17 (0.092) -1.82 Error Covariance for X32 and X19 = 0.34 (0.092) 3.70 Error Covariance for X32 and X110 = 0.34 (0.092) 3.73 Error Covariance for X41 and Y4 = 0.50 (0.092) 5.47 Error Covariance for X41 and X11 = -0.44 (0.092) -4.81 Error Covariance for X41 and X12 = -0.37 (0.092) -4.00 Error Covariance for X41 and X14 = -0.27 (0.092) -2.90 Error Covariance for X41 and X16 = 0.26 (0.092) 2.81
Lampiran 6 (lanjutan)
Error Covariance for X41 and X19 = 0.50 (0.092) 5.45 Error Covariance for X41 and X110 = 0.43 (0.092) 4.65 Error Covariance for X41 and X21 = -0.29 (0.096) -3.04 Error Covariance for X41 and X22 = 0.31 (0.093) 3.38 Error Covariance for X42 and Y2 = -0.21 (0.090) -2.36 Error Covariance for X42 and Y3 = -0.33 (0.092) -3.55 Error Covariance for X42 and X11 = -0.87 (0.091) -9.51 Error Covariance for X42 and X12 = -0.41 (0.092) -4.46 Error Covariance for X42 and X15 = -0.48 (0.092) -5.21
Lampiran 6 (lanjutan)
Error Covariance for X42 and X22 = 0.47 (0.097) 4.82
KEPUASAN = 0.49*PRODUK + 0.080*HARGA + 0.20*TEMPAT + 0.051*PROMOSI, Errorvar.= 0.71, R² = 0.29
(0.075) (0.088) (0.073) (0.066) 6.49 0.91 2.71 0.77
LOYALITA = 0.27*KEPUASAN, Errorvar.= 1.18, R² = 0.18 (0.044) 6.04
Error Covariance for LOYALITA and KEPUASAN = -0.47
Covariance Matrix of Independent Variables PRODUK HARGA TEMPAT PROMOSI --- --- --- --- PRODUK 1.00 HARGA 0.23 - - (0.05) 4.13 TEMPAT -0.14 0.78 1.00 (0.04) (0.07) -3.62 10.84 PROMOSI -0.14 -0.37 -0.02 1.00 (0.03) (0.07) (0.05) -4.09 -5.66 -0.54
Covariance Matrix of Latent Variables
KEPUASAN LOYALITA PRODUK HARGA TEMPAT PROMOSI --- --- --- --- --- --- KEPUASAN 1.00 LOYALITA -0.20 1.00 PRODUK 0.47 0.13 1.00 HARGA 0.25 0.07 0.23 - - TEMPAT 0.19 0.05 -0.14 0.78 1.00 PROMOSI -0.05 -0.01 -0.14 -0.37 -0.02 1.00
The Modification Indices Suggest to Add the
Path to from Decrease in Chi-Square New Estimate
X21 TEMPAT 13.1 0.39 X22 PRODUK 10.4 0.22 X22 TEMPAT 10.0 0.26 X22 PROMOSI 18.1 -0.64 X42 TEMPAT 8.2 0.51 LOYALITA HARGA 10.3 -1.08
Lampiran 6 (lanjutan)
The Modification Indices Suggest to Add a Covariance between and Decrease in Chi-Square New Estimate
HARGA HARGA 20.5 0.62 X22 X21 40.4 0.58
The Problem used 157552 Bytes (= 0.2% of Available Workspace)
Lampiran 7 Kebaiksuaian Keseluruhan Model Penelitian
Goodness of Fit Statistics Degrees of Freedom = 96
Normal Theory Weighted Least Squares Chi-Square = 53.08 (P = 1.00) Estimated Non-centrality Parameter (NCP) = 0.0
90 Percent Confidence Interval for NCP = (0.0 ; 0.0) Minimum Fit Function Value = 2.11
Population Discrepancy Function Value (F0) = 0.0 90 Percent Confidence Interval for F0 = (0.0 ; 0.0) Root Mean Square Error of Approximation (RMSEA) = 0.0 90 Percent Confidence Interval for RMSEA = (0.0 ; 0.0)
P-Value for Test of Close Fit (RMSEA < 0.05) = 1.00 Expected Cross-Validation Index (ECVI) = 2.72 90 Percent Confidence Interval for ECVI = (2.72 ; 2.72)
ECVI for Saturated Model = 3.53 ECVI for Independence Model = 6.31
Chi-Square for Independence Model with 190 Degrees of Freedom = 711.47 Independence AIC = 751.47 Model AIC = 281.08 Saturated AIC = 420.00 Independence CAIC = 827.22 Model CAIC = 712.86 Saturated CAIC = 1215.37
Root Mean Square Residual (RMR) = 0.055 Standardized RMR = 0.050
Goodness of Fit Index (GFI) = 0.97 Adjusted Goodness of Fit Index (AGFI) = 0.93 Parsimony Goodness of Fit Index (PGFI) = 0.44
Normed Fit Index (NFI) = 0.65 Non-Normed Fit Index (NNFI) = 0.41 Parsimony Normed Fit Index (PNFI) = 0.33
Comparative Fit Index (CFI) = 0.70 Incremental Fit Index (IFI) = 0.75 Relative Fit Index (RFI) = 0.30
ABSTRACT
ASRUL KOES. Analysis of Farmers Attitude, Satisfaction and Loyalty Toward the Use of Composite Corn Seed in South Sulawesi. Supervised by RITA NURMALINA and HARMINI
Corn is a strategic commodity in developing agriculture in Indonesia. Increasing national corn production could be achieved by increasing productivity, planting area and use of high yielding varieties. Seed producers are expected to provide seeds of varieties that meet the needs and preferences of farmers. The main factor to be considered in the development of corn high yielding varieties is farmers preference to select and use the appropriate seeds. The use of composite corn seed is an alternative way to increase corn production in South Sulawesi. The purpose of this study are: 1) identify the characteristics, attitudes and behaviours of farmers toward the use of corn seed, 2) analyze the latent variable and dominant indicator variable in building farmers satisfaction and loyalty, and 3) analyze the relationship between farmers satisfaction and loyalty in using composite corn seed. Type of data collected is primary data obtained by survey method using questionnaires. The respondents of this study are 40 corn farmers (ever use local, composite and hybrid corn). Data are analyzed with Fishbein multi attributes approach to determine farmer’s attitude. The other 120 farmers who use composite corn seeds are taken and analyzed using Structural Equation Modeling (SEM) approach to determine relationship between satisfaction and loyalty. The results show that farmer’s attitudes toward composite corn seed tend to be better than those to hybrid corn seed and local corn seed. Based on the SEM analysis, satisfaction variables have relationship with farmers loyalty in the use of composite corn seed in South Sulawesi.
Keywords: attitude, behaviour satisfaction, loyalty, composite corn seed,
RINGKASAN
ASRUL KOES. Analisis Sikap, Kepuasan dan Loyalitas Petani terhadap Penggunaan Benih Unggul Jagung Komposit di Sulawesi Selatan. Dibimbing oleh RITA NURMALINA dan HARMINI
Jagung termasuk komoditas strategis dalam pembangunan pertanian Indonesia. Upaya untuk meningkatkan produksi jagung nasional adalah dengan peningkatan produktivitas dan perluasan areal. Dari aspek teknis, teknologi yang digunakan adalah penggunaan benih unggul. Penggunaan benih bermutu merupakan kunci sukses pertama dalam usahatani jagung. Para produsen benih harus dapat menciptakan varietas yang sesuai kebutuhan dan keinginan petani. Faktor utama yang menjadi pertimbangan dalam pengembangan varietas unggul jagung pada suatu daerah adalah preferensi dan keinginan petani untuk memilih dan menggunakan benih unggul yang sesuai. Namun petani sebagai pengguna, mengalami berbagai kendala dalam memanfaatkan benih unggul/ bermutu. Rendahnya penggunaan benih berlabel (bermutu) ditingkat petani masih menjadi kendala utama dalam peningkatan produksi. Di samping itu, harga benih yang dianggap mahal bagi sebagian petani masih merupakan masalah sehingga melakukan regenerasi benih sendiri. Penggunaan benih unggul jagung komposit merupakan alternatif peningkatan produksi jagung dan penyebarannya telah menjangkau hampir seluruh kabupaten di Sulawesi Selatan. Selain itu, setiap tahun persentase penggunaan masing-masing benih unggul jagung komposit berubah. Munculnya varietas-varietas unggul baru yang dikeluarkan oleh pemerintah maupun perusahaan multinasional tentunya berdampak kepada perilaku petani dalam penggunaan varietas unggul mengingat perbedaan preferensi petani terhadap varietas di setiap wilayah tidak sama. Tentunya akan berimbas pada penggunaan benih itu sendiri. Semua ini tidak lepas dari kondisi demografi, ekonomi, sosial, budaya, keluarga, psikologis dan faktor-faktor lainnya. Petani memiliki karakteristik yang berbeda dan mengalami proses yang kompleks dalam memaksimalkan kepuasannya. Demikian juga dengan perilakunya. Hal tersebut diduga karena adanya perbedaan sikap dan kepuasan petani terhadap ketersediaan varietas unggul jagung komposit. Kondisi tersebut tentunya akan membentuk sikap petani dalam menggunakan benih varietas unggul sehingga petani mengevaluasi benih yang dapat memuaskan serta memenuhi kebutuhannya.
Penelitian ini bertujuan untuk: 1) mengidentifikasi karakteristik dan menganalisis sikap serta perilaku petani terhadap penggunaan benih jagung komposit di Sulawesi Selatan; 2) menganalisis faktor dominan (variabel laten dan variabel indikator) pembentuk kepuasan dan loyalitas petani terhadap penggunaan benih unggul jagung komposit di Sulawesi Selatan; dan 3) menganalisis hubungan antara kepuasan dan loyalitas petani terhadap penggunaan benih unggul jagung komposit di Sulawesi Selatan. Untuk menjawab tujuan tersebut dilakukan analisis sikap, perilaku, kepuasan loyalitas petani terahap penggunaan benih unggul jagung komposit di Sulawesi Selatan. Pemilihan Provinsi Sulawesi Selatan sebagai lokasi penelitian dilakukan secara purposive. Jenis data yang dikumpulkan berupa data primer dengan metode survei yang menggunakan
kuesioner. Pengolahan data dalam penelitian ini menggunakan analisis deskriptif untuk mempermudah pemahaman mengenai karakteristik petani. Sebanyak 40 orang petani dianalisis sikapnya (pernah menggunakan jagung lokal, jagung komposit dan jagung hibrida) dengan menggunakan analisis mutiatribut Fishbein. Sementara 120 orang petani yang menggunakan benih jagung komposit diambil untuk analisis kepuasan dan loyalitas. Data diperoleh dianalisis dengan pendekatan multiatribut Fishbein untuk mengetahui sikap petani, sementara hubungan kepuasan dan loyalitas dianalisis dengan model persamaan struktural
(structural equation modeling).
Karakteristik petani responden didominasi umur produktif sebanyak 80,75 persen dengan proporsi responden laki-laki (100 persen). Sedangkan untuk status pernikahan sebanyak 98,80 persen yang telah menikah. Dilihat dari tingkat pendidikan, pada umumnya petani responden berpendidikan SD dengan persentase 35,00 persen dan menjadikan usahatani jagung sebagai perkerjaan utama sebesar 88,33 persen. Pengalaman petani responden yang menggunakan benih jagung komposit sebesar 57,50 persen (5 – 10 tahun), sementara jagung hibrida persentasenya sebesar 49,17 persen (5 – 10 tahun), dan untuk jagung lokal sebesar 39,17 persen (< 5 tahun). Status lahan garapan sebagian besar merupakan pemilik (82,50%) dengan luasan lahan berkisar 0,5 – 1,0 ha (50,00%). Budidaya jagung yang dilakukan dalam setahun dilakukan sebanyak dua kali tanam sebesar 62,50 persen, sedangkan yang menanam jagung tiga kali dalam setahun sebesar 37,50 persen. Pola tanam “padi-jagung-jagung” umumnya dilakukan dan memberikan kontribusi terbesar sebanyak 54,20 persen dan pola tanam “jagung- jagung-jagung” sebanyak 45,80 persen. Sebagian besar petani responden sebagai pemilik lahan (82,50%) dan sisanya sebagai penggarap (17,50%), dan luas lahan yang dimilikinya antara 0,5 – 1,0 ha sebesar 50,00 persen. Hasil analisis sikap (A0) dengan pendekatan multiatribut Fishbein menunjukkan bahwa diantara tiga jenis jagung yang dibandingkan, sikap petani terhadap benih jagung komposit (23,79) lebih tinggi dibandingkan dengan benih jagung hibrida (15,80) dan jagung lokal (-6,97). Hal ini berarti bahwa sikap petani responden terhadap benih jagung komposit cenderung lebih baik jika dibandingkan dengan benih jagung hibrida dan benih jagung lokal. Atribut yang memiliki tingkat kepentingan tertinggi adalah “produktivitas (hasil panen), sedangkan yang terendah adalah “adanya pedum/juknis/leaflet/brosur”. Dari hasil tersebut menunjukkan bahwa sikap petani responden benih jagung komposit dianggap lebih memenuhi harapan dan keinginan petani responden. Selain itu, perilaku petani dalam menggunakan benih unggul jagung komposit lebih disebabkan oleh karena benih jenis komposit termasuk benih jagung unggul yang memberikan jaminan kualitas yang lebih baik, daya beli petani yang tinggi dan memberikan keuntungan yang lebih tinggi.
Hasil analisis kepuasan dan loyalitas untuk hubungan antar setiap variabel (laten dan indikator) menunjukkan bahwa variabel laten bauran pemasaran berpengaruh positif dengan tingkat kepuasan petani. Namun, jika dilihat dari tingkat signifikansinya, maka hanya variabel laten produk dan tempat yang berpengaruh nyata terhadap kepuasan petani dalam menggunakan benih jagung komposit. Variabel indikator yang berpengaruh positif memiliki keeratan dan merefleksikan variabel latennya. Hasil pendugaan hubungan antara variabel laten dengan variabel indikatornya memperlihatkan bahwa terdapat beberapa variabel indikator yang merefleksikan variabel latennya. Variabel indikator yang
