Universitas Sumatera Utara

Lampiran 1. Produksi Bawang Merah Kabupaten/Kota di Provinsi Sumatera Utara No Kabupaten/Kota Tahun Tahun Tahun Tahun Rata-rata/tahun (Ton) 2008 2009 2010 2011 1 Medan - - - - - 2 Langkat - 15 - - 3.75 3 Deli Serdang 62 30 - - 69.5 4 Simalungun 6,488 5,284 4,772 5,071 17811.75 5 Tanah Karo 1,625 691 809 953 3,363 6 Asahan - - - - - 7 Labuhan Batu - - - - - 8 Tapanuli Utara 483 426 308 61 1232.25 9 Tapanuli Tengah - - - - - 10 Tapanuli Selatan 60 65 17 54 155.5 11 Nias - - - - - 12 Dairi 950 2,150 257 2,180 3902 13 Tebing Tinggi - - - - - 14 Tanjung Balai - - - - - 15 Binjai - - - - - 16 P.Siantar - - - - - 17 Tobasa 625 704 554 1,298 2207.5 18 Madina 20 13-7 34.75 19 P.Sidempuan 33 74 42-117.5 20 Serdang Bedagai - - - - - 21 Batu Bara - - - - - 22 Padang Lawas Utara - 13 147 23 165.75 23 P.Lawas - - - - - 24 Samosir 897 2,070 1,665 1,679 5051.75 25 Humb.Hasundutan 828 1,120 842 1,123 3070.75 26 Pakpak Barat - - - - - 27 Nias Selatan - - - - - Jumlah 12,071 12,655 9,413 12,449 37,186 Sumber : Dinas Pertanian Provinsi Sumatera Utara, 2012

Lampiran 2. Karateristik Konsumen Bawang Merah No.Responden Umur Pekerjaan Pendidikan Terakhir Jumlah Tanggungan Pendapatan Responden (Tahun) (Jiwa) (Rupiah) 1 48 Pedagang SMA 4 5.000.000 2 50 Wiraswasta SMA 3 6.000.000 3 38 Pedagang SMP 3 3.000.000 4 43 IRT D3 3 4.000.000 5 40 Wiraswasta S1 2 4.000.000 6 46 Wiraswasta SMA 2 3.000.000 7 28 IRT SMA 1 1.500.000 8 30 Pedagang SMP 2 1.000.000 9 35 Pedagang SMP 3 1.500.000 10 45 IRT SMA 3 3.000.000 11 33 Pedagang D3 1 3.500.000 12 43 Wiraswasta D3 2 4.000.000 13 37 IRT D1 2 1.500.000 14 40 IRT SMA 3 2.000.000 15 50 Wiraswasta S1 3 5.000.000 16 48 PNS S1 4 5.000.000 17 44 IRT D3 3 3.000.000 18 40 IRT D1 2 2.500.000 19 51 Wiraswasta S1 3 4.000.000 20 52 Dokter S1 3 6.000.000

No.Responden Umur Pekerjaan Pendidikan Terakhir Jumlah Tanggungan Pendapatan Responden (Tahun) (Jiwa) (Rupiah) 21 30 IRT SMA 2 1.500.000 22 40 Pegawai Swasta D3 2 3.000.000 23 34 Pegawai Swasta D3 1 2.000.000 24 38 Pegawai Swasta D3 3 3.000.000 25 25 IRT SMP 2 2.000.000 26 26 Pedagang SMA 1 4.000.000 27 35 IRT SMA 2 3.500.000 28 55 Wiraswasta SMA 4 6.000.000 29 49 PNS S1 3 5.000.000 30 50 Wiraswasta SMA 4 6.000.000 31 42 Pegawai Swasta S1 3 3.000.000 32 23 IRT SMA 2 1.000.000 33 35 Pegawai Swasta SMA 2 1.000.000 34 37 IRT SMA 2 2.000.000 35 24 Pedagang SMA 2 1.500.000 36 25 IRT D1 4 1.500.000 37 31 IRT SMA 3 1.000.000 38 45 IRT SMA 3 3.000.000 39 50 Wiraswasta D3 3 5.000.000 40 52 Wiraswasta S1 2 5.500.000

No.Responden Umur Pekerjaan Pendidikan Terakhir Jumlah Tanggungan Pendapatan Responden (Tahun) (Jiwa) (Rupiah) 41 38 IRT SMA 4 1.000.000 42 23 IRT SMP 2 1.000.000 43 25 IRT D3 3 5.000.000 44 47 PNS S1 4 5.000.000 45 30 Pedagang SMP 3 3.000.000 46 30 Pegawai Swasta SMA 2 2.500.000 47 42 Wiraswasta SMA 2 4.000.000 48 28 IRT SMA 3 900.000 49 23 IRT S1 2 1.500.000 50 24 Pedagang SMA 2 1.000.000 51 27 Pegawai Swasta D1 1 2.000.000 52 25 Pedagang SMA 3 1.500.000 53 33 Pegawai Swasta SMA 1 1.000.000 54 37 Pedagang SMA 1 2.000.000 55 23 Pegawai Swasta SMA 2 1.500.000 56 42 Pedagang D3 1 2.000.000 57 44 Guru S1 4 4.000.000 58 50 Guru S1 3 5.000.000 59 33 Pegawai Swasta D3 2 3.000.000

60 31 Pegawai Swasta S1 1 2.500.000 No.Responden Umur Pekerjaan Pendidikan Terakhir Jumlah Tanggungan Pendapatan Responden (Tahun) (Jiwa) (Rupiah) 62 51 Guru S1 3 5.500.000 63 44 Pegawai Swasta D3 1 3.000.000 64 29 IRT D3 2 1.000.000 65 26 IRT SMP 3 900.000 66 30 Wiraswasta SMA 2 3.000.000 67 28 Pedagang SMA 2 1.500.000 68 32 IRT SMA 3 1.500.000 69 25 Pedagang SMA 1 1.000.000 70 27 IRT SMA 2 1.000.000 71 31 IRT SMA 2 1.500.000 72 30 Pedagang D3 2 3.000.000 73 40 Pedagang SMA 3 2.000.000 74 44 Pedagang SMA 3 1.500.000 75 45 Pegawai Swasta D1 2 2.000.000 76 37 Pengasuh D1 3 2.500.000 77 35 Pegawai Swasta SMA 2 1.000.000 78 33 Pegawai Swasta SMA 1 1.500.000 79 28 Pegawai Swasta D3 2 1.500.000

80 40 Bidan D4 3 3.000.000 No.Responden Umur Pekerjaan Pendidikan Terakhir Jumlah Tanggungan Pendapatan Responden (Tahun) (Jiwa) (Rupiah) 83 24 Pegawai Swasta SMA 1 1.000.000 84 25 Pedagang D3 2 1.500.000 85 40 Pegawai Swasta SMP 2 2.000.000 86 48 Pegawai Swasta SMA 2 2.000.000 87 30 IRT SMA 1 1.500.000 88 50 Guru S1 3 4.000.000 89 50 IRT D3 4 3.800.000 90 50 Guru S1 2 5.000.000 91 52 IRT SMA 2 2.000.000 92 33 Pedagang SMA 3 1.000.000 93 34 IRT SMA 2 1.500.000 94 45 IRT SMP 4 1.000.000 95 39 IRT SMP 2 1.500.000 96 28 Pedagang SMA 2 1.000.000 97 33 Pedagang SMA 3 1.500.000 98 40 IRT SMA 3 1.000.000 99 38 PNS S1 2 5.000.000 100 53 Wiraswasta S1 3 6.000.000

No.Responden Umur Pekerjaan Pendidikan Terakhir Jumlah Tanggungan Pendapatan Responden (Tahun) (Jiwa) (Rupiah) 101 54 Wiraswasta SMA 4 6.000.000

Lampiran.3. Faktor-Faktor Yang Mempengaruhi Permintaan Bawang Merah

No.Responden Jumlah Dibeli (Kilogram) Pendapatan (Rupiah) Harga Rata-Rata Bawang Merah (Rupiah) Jumlah Tanggungan (Jiwa) 1 4 5.000.000 30.000 4 2 5 6.000.000 30.000 3 3 4 3.000.000 30.000 3 4 4 4.000.000 30.000 3 5 4 4.000.000 30.000 2 6 4 3.000.000 30.000 2 7 2 1.500.000 20.000 1 8 2 1.000.000 20.000 2 9 2 1.500.000 28.000 3 10 5 3.000.000 20.000 3 11 4 3.500.000 20.000 1 12 4 4.000.000 28.000 2 13 3 1.500.000 28.000 2 14 4 2.000.000 20.000 3 15 5 5.000.000 25.000 3 16 5 5.000.000 20.000 4 17 5 3.000.000 25.000 3 18 4 2.500.000 20.000 2 19 5 4.000.000 25.000 3

20 5 6.000.000 35.000 3 No.Responden Jumlah Dibeli Pendapatan Harga Rata-Rata Bawang Jumlah Tanggungan (Kilogram) (Rupiah) Merah (Rupiah) (Jiwa) 21 3 1.500.000 28.000 2 22 4 3.000.000 28.000 2 23 2 2.000.000 30.000 1 24 4 3.000.000 20.000 3 25 2 2.000.000 30.000 2 26 2 4.000.000 30.000 1 27 4 3.500.000 20.000 2 28 6 6.000.000 30.000 4 29 4 5.000.000 28.000 3 30 6 6.000.000 30.000 4 31 4 3.000.000 25.000 3 32 2 1.000.000 30.000 2 33 3 1.000.000 20.000 2 34 4 2.000.000 20.000 2 35 2 1.500.000 25.000 2 36 3 1.500.000 20.000 4 37 4 1.000.000 20.000 3 38 5 3.000.000 25.000 3 39 5 5.000.000 20.000 3

40 6 5.500.000 20.000 2 No.Responden Jumlah Dibeli Pendapatan Harga Rata-Rata Bawang Jumlah Tanggungan (Kilogram) (Rupiah) Merah (Rupiah) (Jiwa) 41 2 1.000.000 20.000 4 42 2 1.000.000 20.000 2 43 5 5.000.000 30.000 3 44 6 5.000.000 30.000 4 45 3 3.000.000 28.000 3 46 3 2.500.000 28.000 2 47 4 4.000.000 20.000 2 48 2 900.000 30.000 3 49 2 1.500.000 20.000 2 50 2 1.000.000 20.000 2 51 4 2.000.000 20.000 1 52 2 1.500.000 30.000 3 53 2 1.000.000 20.000 1 54 3 2.000.000 28.000 1 55 2 1.500.000 20.000 2 56 4 2.000.000 30.000 1 57 4 4.000.000 30.000 4 58 6 5.000.000 30.000 3 59 3 3.000.000 30.000 2

60 2 2.500.000 20.000 1 No.Responden Jumlah Dibeli Pendapatan Harga Rata-Rata Bawang Jumlah Tanggungan (Kilogram) (Rupiah) Merah (Rupiah) (Jiwa) 61 5 4.000.000 30.000 2 62 6 5.500.000 28.000 3 63 2 3.000.000 30.000 1 64 2 1.000.000 20.000 2 65 2 900.000 20.000 3 66 5 3.000.000 20.000 2 67 2 1.500.000 30.000 2 68 3 1.500.000 20.000 3 69 2 1.000.000 20.000 1 70 2 1.000.000 20.000 2 71 2 1.500.000 25.000 2 72 3 3.000.000 30.000 2 73 4 2.000.000 20.000 3 74 4 1.500.000 20.000 3 75 4 2.000.000 20.000 2 76 2 2.500.000 28.000 3 77 2 1.000.000 20.000 2 78 2 1.500.000 28.000 1 79 3 1.500.000 28.000 2

80 4 3.000.000 28.000 3 No.Responden Jumlah Dibeli Pendapatan Harga Rata-Rata Bawang Jumlah Tanggungan (Kilogram) (Rupiah) Merah (Rupiah) (Jiwa) 81 4 3.000.000 30.000 2 82 2 1.000.000 20.000 3 83 2 1.000.000 20.000 1 84 2 1.500.000 30.000 2 85 2 2.000.000 30.000 2 86 2 2.000.000 28.000 2 87 3 1.500.000 20.000 1 88 5 4.000.000 20.000 3 89 5 3.800.000 20.000 4 90 5 5.000.000 30.000 2 91 2 2.000.000 30.000 2 92 2 1.000.000 20.000 3 93 3 1.500.000 20.000 2 94 2 1.000.000 20.000 4 95 3 1.500.000 20.000 2 96 2 1.000.000 20.000 2 97 2 1.500.000 20.000 3 98 4 1.000.000 20.000 3 99 5 5.000.000 30.000 2

100 6 6.000.000 28.000 3 No.Responden Jumlah Dibeli Pendapatan Harga Rata-Rata Bawang Jumlah Tanggungan (Kilogram) (Rupiah) Merah (Rupiah) (Jiwa) 101 5 6.000.000 28.000 4

Lampiran. 4 Hasil Output Analisis Regresi Berganda Faktor-Faktor Yang Mempengaruhi Permintaan Bawang Merah Descriptive Statistics Mean Std. Deviation N permintaabbawangmerah 3.4356 1.32224 101 pendapatan_penerimaan_bulan an 2.6990E6 1.56943E6 101 jumlah_tanggungan 2.4158.86333 101 harga_bawang 2.4812E4 4636.18997 101 Correlations permintaabbawang pendapatan_pener jumlah_tanggunga merah imaan_bulanan n harga_bawang Pearson Correlation permintaabbawangmerah 1.000.822.435.175 pendapatan_penerimaan_bulan an.822 1.000.377.444 jumlah_tanggungan.435.377 1.000.060 harga_bawang.175.444.060 1.000 Sig. (1-tailed) permintaabbawangmerah..000.000.040

pendapatan_penerimaan_bulan an.000..000.000 jumlah_tanggungan.000.000..277 harga_bawang.040.000.277. N permintaabbawangmerah 101 101 101 101 pendapatan_penerimaan_bulan an 101 101 101 101 jumlah_tanggungan 101 101 101 101 harga_bawang 101 101 101 101 Variables Entered/Removed b Variables Model Variables Entered Removed Method 1 harga_bawang, jumlah_tanggunga n, pendapatan_pener imaan_bulanan a. Enter a. All requested variables entered. b. Dependent Variable: permintaabbawangmerah

Model Summary b Std. Error of the Change Statistics Model R R Square Adjusted R Square Estimate R Square Change F Change df1 df2 Sig. F Change Durbin-Watson 1.856 a.732.724.69451.732 88.487 3 97.000 2.048 a. Predictors: (Constant), harga_bawang, jumlah_tanggungan, pendapatan_penerimaan_bulanan b. Dependent Variable: permintaabbawangmerah ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression 128.044 3 42.681 88.487.000 a Residual 46.788 97.482 Total 174.832 100 a. Predictors: (Constant), harga_bawang, jumlah_tanggungan, pendapatan_penerimaan_bulanan b. Dependent Variable: permintaabbawangmerah

Coefficients a Unstandardized Coefficients Standardized Coefficients 95% Confidence Interval for B Correla Model B Std. Error Beta t Sig. Lower Bound Upper Bound Zero-order Pa 1 (Constant) 2.569.435 5.905.000 1.706 3.433 pendapatan_penerimaan_bulan an 7.374E-7.000.875 13.736.000.000.000.822 jumlah_tanggungan.182.088.119 2.079.040.008.356.435 harga_bawang -6.302E-5.000 -.221-3.737.000.000.000.175 a. Dependent Variable: permintaabbawangmerah Coefficient Correlations a jumlah_tanggunga pendapatan_pener Model harga_bawang n imaan_bulanan 1 Correlations harga_bawang 1.000.130 -.456 jumlah_tanggungan.130 1.000 -.392 pendapatan_penerimaan_bulan an -.456 -.392 1.000

Covariances harga_bawang 2.844E-10 1.916E-7-4.130E-13 jumlah_tanggungan 1.916E-7.008-1.841E-9 pendapatan_penerimaan_bulan an -4.130E-13-1.841E-9 2.882E-15 a. Dependent Variable: permintaabbawangmerah Collinearity Diagnostics a Variance Proportions Dimensi pendapatan_pener jumlah_tanggunga Model on Eigenvalue Condition Index (Constant) imaan_bulanan n harga_bawang 1 1 3.747 1.000.00.01.01.00 2.160 4.833.03.79.02.01 3.079 6.872.02.02.83.07 4.013 16.750.95.18.14.92 a. Dependent Variable: permintaabbawangmerah Residuals Statistics a

Minimum Maximum Mean Std. Deviation N Predicted Value 1.7802 5.9573 3.4356 1.13157 101 Residual -1.81019 1.66455.00000.68401 101 Std. Predicted Value -1.463 2.228.000 1.000 101 Std. Residual -2.606 2.397.000.985 101 a. Dependent Variable: permintaabbawangmerah Charts

Lampiran.5 Faktor-Faktor Yang Mempengaruhi Permintaan Bawang Merah Logaritma Natural No. Y X1 X2 X3 LNY LNX1 LNX2 LNX3 Responden 1 4.0 5000000.0 30000.0 4.0 1.386294361 15.42494847 10.30895266 1.386294361 2 5.0 6000000.0 30000.0 3.0 1.609437912 15.60727003 10.30895266 1.098612289 3 4.0 3000000.0 30000.0 3.0 1.386294361 14.91412285 10.30895266 1.098612289 4 4.0 4000000.0 30000.0 3.0 1.386294361 15.20180492 10.30895266 1.098612289 5 4.0 4000000.0 30000.0 2.0 1.386294361 15.20180492 10.30895266 0.693147181 6 4.0 3000000.0 30000.0 2.0 1.386294361 14.91412285 10.30895266 0.693147181 7 2.0 1500000.0 20000.0 1.0 0.693147181 14.22097567 9.903487553 0 8 2.0 1000000.0 20000.0 2.0 0.693147181 13.81551056 9.903487553 0.693147181 9 2.0 1500000.0 28000.0 3.0 0.693147181 14.22097567 10.23995979 1.098612289 10 5.0 3000000.0 20000.0 3.0 1.609437912 14.91412285 9.903487553 1.098612289 11 4.0 3500000.0 20000.0 1.0 1.386294361 15.06827353 9.903487553 0 12 4.0 4000000.0 28000.0 2.0 1.386294361 15.20180492 10.23995979 0.693147181 13 3.0 1500000.0 28000.0 2.0 1.098612289 14.22097567 10.23995979 0.693147181 14 4.0 2000000.0 20000.0 3.0 1.386294361 14.50865774 9.903487553 1.098612289

No. Y X1 X2 X3 LNY LNX1 LNX2 LNX3 Responden 15 5.0 5000000.0 25000.0 3.0 1.609437912 15.42494847 10.1266311 1.098612289 16 5.0 5000000.0 20000.0 4.0 1.609437912 15.42494847 9.903487553 1.386294361 17 5.0 3000000.0 25000.0 3.0 1.609437912 14.91412285 10.1266311 1.098612289 18 4.0 2500000.0 20000.0 2.0 1.386294361 14.73180129 9.903487553 0.693147181 19 5.0 4000000.0 25000.0 3.0 1.609437912 15.20180492 10.1266311 1.098612289 20 5.0 6000000.0 35000.0 3.0 1.609437912 15.60727003 10.46310334 1.098612289 21 3.0 1500000.0 28000.0 2.0 1.098612289 14.22097567 10.23995979 0.693147181 22 4.0 3000000.0 28000.0 2.0 1.386294361 14.91412285 10.23995979 0.693147181 23 2.0 2000000.0 30000.0 1.0 0.693147181 14.50865774 10.30895266 0 24 4.0 3000000.0 20000.0 3.0 1.386294361 14.91412285 9.903487553 1.098612289 25 2.0 2000000.0 30000.0 2.0 0.693147181 14.50865774 10.30895266 0.693147181 26 2.0 4000000.0 30000.0 1.0 0.693147181 15.20180492 10.30895266 0 27 4.0 3500000.0 20000.0 2.0 1.386294361 15.06827353 9.903487553 0.693147181 28 6.0 6000000.0 30000.0 4.0 1.791759469 15.60727003 10.30895266 1.386294361 29 4.0 5000000.0 28000.0 3.0 1.386294361 15.42494847 10.23995979 1.098612289

No. Y X1 X2 X3 LNY LNX1 LNX2 LNX3 Responden 30 6.0 6000000.0 30000.0 4.0 1.791759469 15.60727003 10.30895266 1.386294361 31 4.0 3000000.0 25000.0 3.0 1.386294361 14.91412285 10.1266311 1.098612289 32 2.0 1000000.0 30000.0 2.0 0.693147181 13.81551056 10.30895266 0.693147181 33 3.0 1000000.0 20000.0 2.0 1.098612289 13.81551056 9.903487553 0.693147181 34 4.0 2000000.0 20000.0 2.0 1.386294361 14.50865774 9.903487553 0.693147181 35 2.0 1500000.0 25000.0 2.0 0.693147181 14.22097567 10.1266311 0.693147181 36 3.0 1500000.0 20000.0 4.0 1.098612289 14.22097567 9.903487553 1.386294361 37 4.0 1000000.0 20000.0 3.0 1.386294361 13.81551056 9.903487553 1.098612289 38 5.0 3000000.0 25000.0 3.0 1.609437912 14.91412285 10.1266311 1.098612289 39 5.0 5000000.0 20000.0 3.0 1.609437912 15.42494847 9.903487553 1.098612289 40 6.0 5500000.0 20000.0 2.0 1.791759469 15.52025865 9.903487553 0.693147181 41 2.0 1000000.0 20000.0 4.0 0.693147181 13.81551056 9.903487553 1.386294361 42 2.0 1000000.0 20000.0 2.0 0.693147181 13.81551056 9.903487553 0.693147181 43 5.0 5000000.0 30000.0 3.0 1.609437912 15.42494847 10.30895266 1.098612289 44 6.0 5000000.0 30000.0 4.0 1.791759469 15.42494847 10.30895266 1.386294361

No. Y X1 X2 X3 LNY LNX1 LNX2 LNX3 Responden 45 3.0 3000000.0 28000.0 3.0 1.098612289 14.91412285 10.23995979 1.098612289 46 3.0 2500000.0 28000.0 2.0 1.098612289 14.73180129 10.23995979 0.693147181 47 4.0 4000000.0 20000.0 2.0 1.386294361 15.20180492 9.903487553 0.693147181 48 2.0 900000.0 30000.0 3.0 0.693147181 13.71015004 10.30895266 1.098612289 49 2.0 1500000.0 20000.0 2.0 0.693147181 14.22097567 9.903487553 0.693147181 50 2.0 1000000.0 20000.0 2.0 0.693147181 13.81551056 9.903487553 0.693147181 51 4.0 2000000.0 20000.0 1.0 1.386294361 14.50865774 9.903487553 0 52 2.0 1500000.0 30000.0 3.0 0.693147181 14.22097567 10.30895266 1.098612289 53 2.0 1000000.0 20000.0 1.0 0.693147181 13.81551056 9.903487553 0 54 3.0 2000000.0 28000.0 1.0 1.098612289 14.50865774 10.23995979 0 55 2.0 1500000.0 20000.0 2.0 0.693147181 14.22097567 9.903487553 0.693147181 56 4.0 2000000.0 30000.0 1.0 1.386294361 14.50865774 10.30895266 0 57 4.0 4000000.0 30000.0 4.0 1.386294361 15.20180492 10.30895266 1.386294361 58 6.0 5000000.0 30000.0 3.0 1.791759469 15.42494847 10.30895266 1.098612289 59 3.0 3000000.0 30000.0 2.0 1.098612289 14.91412285 10.30895266 0.693147181

No. Y X1 X2 X3 LNY LNX1 LNX2 LNX3 Responden 60 2.0 2500000.0 20000.0 1.0 0.693147181 14.73180129 9.903487553 0 61 5.0 4000000.0 30000.0 2.0 1.609437912 15.20180492 10.30895266 0.693147181 62 6.0 5500000.0 28000.0 3.0 1.791759469 15.52025865 10.23995979 1.098612289 63 2.0 3000000.0 30000.0 1.0 0.693147181 14.91412285 10.30895266 0 64 2.0 1000000.0 20000.0 2.0 0.693147181 13.81551056 9.903487553 0.693147181 65 2.0 900000.0 20000.0 3.0 0.693147181 13.71015004 9.903487553 1.098612289 66 5.0 3000000.0 20000.0 2.0 1.609437912 14.91412285 9.903487553 0.693147181 67 2.0 1500000.0 30000.0 2.0 0.693147181 14.22097567 10.30895266 0.693147181 68 3.0 1500000.0 20000.0 3.0 1.098612289 14.22097567 9.903487553 1.098612289 69 2.0 1000000.0 20000.0 1.0 0.693147181 13.81551056 9.903487553 0 70 2.0 1000000.0 20000.0 2.0 0.693147181 13.81551056 9.903487553 0.693147181 71 2.0 1500000.0 25000.0 2.0 0.693147181 14.22097567 10.1266311 0.693147181 72 3.0 3000000.0 30000.0 2.0 1.098612289 14.91412285 10.30895266 0.693147181 73 4.0 2000000.0 20000.0 3.0 1.386294361 14.50865774 9.903487553 1.098612289 74 4.0 1500000.0 20000.0 3.0 1.386294361 14.22097567 9.903487553 1.098612289

No. Y X1 X2 X3 LNY LNX1 LNX2 LNX3 Responden 75 4.0 2000000.0 20000.0 2.0 1.386294361 14.50865774 9.903487553 0.693147181 76 2.0 2500000.0 28000.0 3.0 0.693147181 14.73180129 10.23995979 1.098612289 77 2.0 1000000.0 20000.0 2.0 0.693147181 13.81551056 9.903487553 0.693147181 78 2.0 1500000.0 28000.0 1.0 0.693147181 14.22097567 10.23995979 0 79 3.0 1500000.0 28000.0 2.0 1.098612289 14.22097567 10.23995979 0.693147181 80 4.0 3000000.0 28000.0 3.0 1.386294361 14.91412285 10.23995979 1.098612289 81 4.0 3000000.0 30000.0 2.0 1.386294361 14.91412285 10.30895266 0.693147181 82 2.0 1000000.0 20000.0 3.0 0.693147181 13.81551056 9.903487553 1.098612289 83 2.0 1000000.0 20000.0 1.0 0.693147181 13.81551056 9.903487553 0 84 2.0 1500000.0 30000.0 2.0 0.693147181 14.22097567 10.30895266 0.693147181 85 2.0 2000000.0 30000.0 2.0 0.693147181 14.50865774 10.30895266 0.693147181 86 2.0 2000000.0 28000.0 2.0 0.693147181 14.50865774 10.23995979 0.693147181 87 3.0 1500000.0 20000.0 1.0 1.098612289 14.22097567 9.903487553 0 88 5.0 4000000.0 20000.0 3.0 1.609437912 15.20180492 9.903487553 1.098612289 89 5.0 3800000.0 20000.0 4.0 1.609437912 15.15051162 9.903487553 1.386294361

No. Y X1 X2 X3 LNY LNX1 LNX2 LNX3 Responden 90 5.0 5000000.0 30000.0 2.0 1.609437912 15.42494847 10.30895266 0.693147181 91 2.0 2000000.0 30000.0 2.0 0.693147181 14.50865774 10.30895266 0.693147181 92 2.0 1000000.0 20000.0 3.0 0.693147181 13.81551056 9.903487553 1.098612289 93 3.0 1500000.0 20000.0 2.0 1.098612289 14.22097567 9.903487553 0.693147181 94 2.0 1000000.0 20000.0 4.0 0.693147181 13.81551056 9.903487553 1.386294361 95 3.0 1500000.0 20000.0 2.0 1.098612289 14.22097567 9.903487553 0.693147181 96 2.0 1000000.0 20000.0 2.0 0.693147181 13.81551056 9.903487553 0.693147181 97 2.0 1500000.0 20000.0 3.0 0.693147181 14.22097567 9.903487553 1.098612289 98 4.0 1000000.0 20000.0 3.0 1.386294361 13.81551056 9.903487553 1.098612289 99 5.0 5000000.0 30000.0 2.0 1.609437912 15.42494847 10.30895266 0.693147181 100 6.0 6000000.0 28000.0 3.0 1.791759469 15.60727003 10.23995979 1.098612289 101 5.0 6000000.0 28000.0 4.0 1.609437912 15.60727003 10.23995979 1.386294361 Lampiran.6 Hasil Output Analisis Logaritma Natural Faktor-Faktor Yang Mempengaruhi Permintaan Bawang Merah

d i m e n s i o n 0 Variables Entered/Removed b Model Variables Entered Variables Removed Method 1 tanggungan, harga, pendapatan a. Enter a. All requested variables entered. b. Dependent Variable: Permintaan

d i m e n s i o n 0 Model Model Summary b R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 1.843 a.710.701.21652 2.106 a. Predictors: (Constant), tanggungan, harga, pendapatan b. Dependent Variable: Permintaan ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression 11.128 3 3.709 79.122.000 a

Residual 4.548 97.047 Total 15.676 100 a. Predictors: (Constant), tanggungan, harga, pendapatan b. Dependent Variable: Permintaan Coefficients a Model Unstandardized Coefficients Standardized Coefficients B Std. Error Beta t Sig. 1 (Constant) -1.961 1.161-1.689.094 pendapatan.568.043.856 13.292.000 harga -.528.130 -.252-4.058.000 tanggungan.180.056.184 3.216.002 a. Dependent Variable: Permintaan Coefficients a Model Collinearity Statistics Tolerance VIF 1 (Constant) pendapatan.721 1.387 harga.778 1.286

tanggungan.918 1.090 a. Dependent Variable: Permintaan Charts