lanai anal anal a-DI anal · lanai anal anal a-DI anal . Created Date: 7/12/2016 2:27:37 PM
Cont Oh Anal is is Linear Berg and A
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CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDA HAMA WERENG COKLAT DI 24 LOKASI PENGAMATAN Lokasi % Luas Rata-rata populasi per rumpun Varietas Tan. Muda Pop. Pop. Pop. Peka <30 hst WBC G0 WBC G1 WBC G2 X1 X2 X3 X4 X5 1 17 1.8 18 75 180 2 15 1.3 14 60 145 3 12.5 0.8 10 50 100 4 12 0.25 9 25 75 5 2.5 0.35 0.2 1 30 6 2 0.4 0.6 1.5 48 7 2 0.2 0.6 5 37 8 0 0 0 0.5 23 9 0 0 0 0 0 10 0 0 0 0 50 11 5 0.3 0.2 21 58 12 10 1.8 7 25 100 13 15 1.8 10 50 160 14 14 1.45 12 60 150 15 12.5 1 15 60 120 16 8 0.75 3 5 20 17 1 0.3 4 25 30 18 1.5 0.48 0.15 5 45 19 2 0.37 0.2 10 10 20 0 0.23 0.6 10 0 21 0 0 0 0 0 22 0 0.5 0 18 70 23 1.7 0.58 0.3 15 80 24 5 0.2 0.7 30 75
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Transcript of Cont Oh Anal is is Linear Berg and A
CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDAHAMA WERENG COKLAT DI 24 LOKASI PENGAMATAN
Lokasi
% Luas Rata-rata populasi per rumpunVarietas Tan. Muda Pop. Pop. Pop.
Peka <30 hst WBC G0 WBC G1 WBC G2X1 X2 X3 X4 X5
1 17 1.8 18 75 1802 15 1.3 14 60 1453 12.5 0.8 10 50 1004 12 0.25 9 25 755 2.5 0.35 0.2 1 306 2 0.4 0.6 1.5 487 2 0.2 0.6 5 378 0 0 0 0.5 239 0 0 0 0 0
10 0 0 0 0 5011 5 0.3 0.2 21 5812 10 1.8 7 25 10013 15 1.8 10 50 16014 14 1.45 12 60 15015 12.5 1 15 60 12016 8 0.75 3 5 2017 1 0.3 4 25 3018 1.5 0.48 0.15 5 4519 2 0.37 0.2 10 1020 0 0.23 0.6 10 021 0 0 0 0 022 0 0.5 0 18 7023 1.7 0.58 0.3 15 8024 5 0.2 0.7 30 75
CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDA
KLTS WBC (ha)
akhir musimY
220 Tahap 1 : Manajemen data200125 1. Susun data untuk setiap variabel berdasarkan lokasi100
10 2. Buah header kolom sesuai dengan variabel yang sesuai2550 3. Buat peubah (notasi variabel) untuk masing-masing variabel,15 X1 = % Luas varietas peka
0 X2 = % luas tanaman muda umur <30 hst10 X3 = Rata-rata populasi WBC per rumpun pada G0 (umur padi <30 hst)
100 X4 = Rata-rata populasi WBC per rumpun pada G1 (umur padi 30-60 hst)150 X5 = Rata-rata populasi WBC per rumpun pada G2 (umur padi 60-90 hst)200 Y = Kumulatif luas tambah serangan (KLTS) yang terjadi sampi akhir musim200150
5010
5000
306015
X3 = Rata-rata populasi WBC per rumpun pada G0 (umur padi <30 hst)X4 = Rata-rata populasi WBC per rumpun pada G1 (umur padi 30-60 hst)X5 = Rata-rata populasi WBC per rumpun pada G2 (umur padi 60-90 hst)Y = Kumulatif luas tambah serangan (KLTS) yang terjadi sampi akhir musim
CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDAHAMA WERENG COKLAT DI 24 LOKASI PENGAMATAN
Tahap 2 : Membuat grafik diagram pencar hubungan setiap variabel independen (X) dengan dependen (Y) KLTS akhir musim
0 10 20 30 40 50 60 70 80
0
20
40
60
80
100
120
140
160
180
200
f(x) = 2.05429633979252 x + 19.6678508514386R² = 0.824211625435798
Column F
Linear (Column F)
G1
G2
0 2 4 6 8 10 12 14 16 18 20
0
10
20
30
40
50
60
70
80
f(x) = 3.76137536895025 x + 6.45778457530423R² = 0.865771575429777
Column E
Linear (Column E)
G0
G1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
0
50
100
150
200
250
f(x) = 114.713555821285 x + 0.848190020654442R² = 0.786584636780675
Column G
Linear (Column G)
% Tan Muda
KL
TS
0 2 4 6 8 10 12 14 16 18
0
50
100
150
200
250
f(x) = 12.0459997575412 x + 2.25915973454288R² = 0.884167133303688
Column G
Linear (Column G)
% Var Peka
KL
TS
Tahap 2 : Membuat grafik diagram pencar hubungan setiap variabel independen (X) dengan dependen (Y) KLTS akhir musim
0 20 40 60 80 100 120 140 160 180 200
0
50
100
150
200
250
f(x) = 1.34123327225418 x − 17.8758598016754R² = 0.865411645225148
Column G
Linear (Column G)
G2
KL
TS
0 10 20 30 40 50 60 70 80
0
20
40
60
80
100
120
140
160
180
200
f(x) = 2.05429633979252 x + 19.6678508514386R² = 0.824211625435798
Column F
Linear (Column F)
G1
G2
0 2 4 6 8 10 12 14 16 18 20
0
20
40
60
80
100
120
140
160
180
200
f(x) = 7.82468921018693 x + 32.5043355776988R² = 0.731739863993295
Column F
Linear (Column F)
G0
G2
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
0
50
100
150
200
250
f(x) = 114.713555821285 x + 0.848190020654442R² = 0.786584636780675
Column G
Linear (Column G)
% Tan Muda
KL
TS
CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDAHAMA WERENG COKLAT DI 24 LOKASI PENGAMATAN
Lokasi
% Luas Rata-rata populasi per rumpunVarietas Tan. Muda Pop. Pop. Pop.
Peka <30 hst WBC G0 WBC G1 WBC G2X1 X2 X3 X4 X5
1 17 1.8 18 75 1802 15 1.3 14 60 1453 12.5 0.8 10 50 1004 12 0.25 9 25 755 2.5 0.35 0.2 1 306 2 0.4 0.6 1.5 487 2 0.2 0.6 5 378 0 0 0 0.5 239 0 0 0 0 0
10 0 0 0 0 5011 5 0.3 0.2 21 5812 10 1.8 7 25 10013 15 1.8 10 50 16014 14 1.45 12 60 15015 12.5 1 15 60 12016 8 0.75 3 5 2017 1 0.3 4 25 3018 1.5 0.48 0.15 5 4519 2 0.37 0.2 10 1020 0 0.23 0.6 10 021 0 0 0 0 022 0 0.5 0 18 7023 1.7 0.58 0.3 15 8024 5 0.2 0.7 30 75
CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDA
KLTS Tahap 3 : Analisis regresi parsial unt setiap variabel independen (X) dengan dependep (Y)
WBC (ha)akhir musim
Y220 1. Hubungan X1 dengan Y
200125 SUMMARY OUTPUT
10010 Regression Statistics
25 Multiple R 0.940302
50 R Square 0.884167
15 Adjusted R 0.878902
0 Standard E 26.75341
10 Observatio 24
100150 ANOVA
200 df SS MS F Significance F
200 Regression 1 120194.2 120194.2 167.9288 8.96E-12
150 Residual 22 15746.39 715.7451
50 Total 23 135940.6
105 CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%
0 Intercept 2.25916 7.660441 0.294913 0.770826 -13.62764 18.14596
0 X Variable 12.046 0.929566 12.95874 8.96E-12 10.1182 13.9738
030 2. Hubngan X2 dengan Y
6015 SUMMARY OUTPUT
Regression Statistics
Multiple R 0.886896
R Square 0.786585
Adjusted R 0.776884
Standard E 36.31417
Observatio 24
ANOVA
df SS MS F Significance F
Regression 1 106928.8 106928.8 81.08536 7.85E-09
Residual 22 29011.82 1318.719
Total 23 135940.6
CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%
Intercept 0.84819 10.82417 0.078361 0.938249 -21.59979 23.29617
X Variable 114.7136 12.73924 9.004741 7.85E-09 88.29396 141.1332
3. Hubungan X3 dengan Y
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.903181
R Square 0.815736
Adjusted R 0.80736
Standard E 33.74299
Observatio 24
ANOVA
df SS MS F Significance F
Regression 1 110891.7 110891.7 97.39393 1.53E-09
Residual 22 25048.96 1138.589
Total 23 135940.6
CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%
Intercept 19.49042 8.6958 2.24136 0.035418 1.45641 37.52442
X Variable 11.91123 1.206954 9.868836 1.53E-09 9.408156 14.4143
Tahap 3 : Analisis regresi parsial unt setiap variabel independen (X) dengan dependep (Y)
4. Hubungan X4 dengan Y
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.891431
R Square 0.794649
Adjusted R 0.785315
Standard E 35.62143
Observatio 24
ANOVA
df SS MS F Significance F
Regression 1 108025.1 108025.1 85.13384 5.11E-09
Residual 22 27915.49 1268.886
Total 23 135940.6
Lower 95.0%Upper 95.0% CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%
-13.62764 18.14596 Intercept 4.986372 10.26761 0.485641 0.632023 -16.30737 26.28012
10.1182 13.9738 X Variable 2.908201 0.315191 9.2268 5.11E-09 2.254535 3.561867
5. Hubungan X5 dengan Y
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.930275
R Square 0.865412
Adjusted R 0.859294
Standard E 28.83813
Observatio 24
ANOVA
df SS MS F Significance F
Regression 1 117644.6 117644.6 141.4614 4.72E-11
Residual 22 18296.03 831.6375
Total 23 135940.6
Lower 95.0%Upper 95.0% CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%
-21.59979 23.29617 Intercept -17.87586 9.570498 -1.867809 0.075168 -37.72388 1.972159
88.29396 141.1332 X Variable 1.341233 0.112768 11.89375 4.72E-11 1.107367 1.5751
Lower 95.0%Upper 95.0%
1.45641 37.52442
9.408156 14.4143
Lower 95.0%Upper 95.0%
-16.30737 26.28012
2.254535 3.561867
Lower 95.0%Upper 95.0%
-37.72388 1.972159
1.107367 1.5751
CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDAHAMA WERENG COKLAT DI 24 LOKASI PENGAMATAN
Lokasi
% Luas Rata-rata populasi per rumpunVarietas Tan. Muda Pop. Pop. Pop.
Peka <30 hst WBC G0 WBC G1 WBC G2X1 X2 X3 X4 X5
1 17 1.8 18 75 1802 15 1.3 14 60 1453 12.5 0.8 10 50 1004 12 0.25 9 25 755 2.5 0.35 0.2 1 306 2 0.4 0.6 1.5 487 2 0.2 0.6 5 378 0 0 0 0.5 239 0 0 0 0 0
10 0 0 0 0 5011 5 0.3 0.2 21 5812 10 1.8 7 25 10013 15 1.8 10 50 16014 14 1.45 12 60 15015 12.5 1 15 60 12016 8 0.75 3 5 2017 1 0.3 4 25 3018 1.5 0.48 0.15 5 4519 2 0.37 0.2 10 1020 0 0.23 0.6 10 021 0 0 0 0 022 0 0.5 0 18 7023 1.7 0.58 0.3 15 8024 5 0.2 0.7 30 75
Rata-rata 5.813043478 0.637391304 4.558695652 22.69565217 66.56521739Skewn 0.598691005 0.966278712 1.007722024 0.904239185 0.668934987
CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDA
KLTS WBC (ha) Tahap 4 : Analisis multi regrasi antara X1, X2, X3 dengan Y
akhir musimY SUMMARY OUTPUT
220200 Regression Statistics125 Multiple R 0.96055100 R Square 0.92266
10 Adjusted R Square 0.9110625 Standard Error 22.927850 Observations 2415
0 ANOVA10 df SS MS F
100 Regression 3 125427 41809 79.5329150 Residual 20 10513.6 525.682200 Total 23 135941200150 CoefficientsStandard Errort Stat P-value
50 Intercept -2.02489 7.18775 -0.28171 0.7810610 %VarPeka X Variable 1 6.55493 2.46119 2.66332 0.01493
5 %TanMud X Variable 2 42.8544 14.5719 2.9409 0.008080 G0 X Variable 3 2.15644 2.29087 0.94132 0.3577700
3060 RESIDUAL OUTPUT15
74.347826087 Observation Predicted YResidualsStandard Residuals0.7286653753 1 225.363 -5.36275 -0.25083
2 182.2 17.8001 0.832553 135.76 -10.7596 -0.503254 106.756 -6.7558 -0.315985 29.7928 -19.7928 -0.925756 29.5206 -4.5206 -0.211447 20.9497 29.0503 1.358748 -2.02489 17.0249 0.796299 -2.02489 2.02489 0.09471
10 -2.02489 12.0249 0.56243
11 44.0374 55.9626 2.6174912 155.757 -5.75742 -0.2692913 195.001 4.99863 0.233814 177.76 22.2397 1.040215 155.113 -5.11272 -0.2391316 89.0247 -39.0247 -1.8252717 26.0121 -16.0121 -0.7489218 28.7011 -23.7011 -1.1085519 27.3724 -27.3724 -1.2802720 9.12549 -9.12549 -0.4268221 -2.02489 2.02489 0.0947122 19.4023 10.5977 0.4956823 34.621 25.379 1.1870324 40.8301 -25.8301 -1.20813
Tahap 4 : Analisis multi regrasi antara X1, X2, X3 dengan Y
Significance F2.731637E-11
Lower 95% Upper 95%Lower 95.0%Upper 95.0%-17.01826419 12.9685 -17.018 12.96851.4209818658 11.6889 1.42098 11.688912.458043251 73.2508 12.458 73.2508-2.622236853 6.93512 -2.6222 6.93512
PROBABILITY OUTPUT
Percentile Y2.0833333333 0
6.25 010.416666667 014.583333333 0
18.75 522.916666667 1027.083333333 10
31.25 1035.416666667 1539.583333333 15
0 2 4 6 8 10 12 14 16 18
-60-40-20
020406080
X Variable 1 Residual Plot
X Variable 1
Res
idu
als
0 2 4 6 8 10 12 14 16 18-500
50100150200250
X Variable 1 Line Fit Plot
Y
Predicted Y
X Variable 1
Y
0 20 40 60 80 100 1200
50100150200250
Normal Probability Plot
Sample Percentile
Y
43.75 2547.916666667 3052.083333333 50
56.25 5060.416666667 6064.583333333 100
68.75 10072.916666667 12577.083333333 150
81.25 15085.416666667 20089.583333333 200
93.75 20097.916666667 220
0 2 4 6 8 10 12 14 16 18
-60-40-20
020406080
X Variable 1 Residual Plot
X Variable 1
Res
idu
als
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
-60
-20
20
60
X Variable 2 Residual Plot
X Variable 2
Res
idu
als
0 2 4 6 8 10 12 14 16 18 20
-60-40-20
020406080
X Variable 3 Residual Plot
X Variable 3
Res
idu
als
0 2 4 6 8 10 12 14 16 18-500
50100150200250
X Variable 1 Line Fit Plot
Y
Predicted Y
X Variable 1
Y
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2-100
0
100
200
300
X Variable 2 Line Fit Plot
Y
Predicted Y
X Variable 2
Y
0 2 4 6 8 10 12 14 16 18 20-100
0
100
200
300
X Variable 3 Line Fit Plot
Y
Predicted Y
X Variable 3
Y
0 20 40 60 80 100 1200
50100150200250
Normal Probability Plot
Sample Percentile
Y
0 2 4 6 8 10 12 14 16 18 20
-60-40-20
020406080
X Variable 3 Residual Plot
X Variable 3
Res
idu
als
0 2 4 6 8 10 12 14 16 18 20-100
0
100
200
300
X Variable 3 Line Fit Plot
Y
Predicted Y
X Variable 3
Y
CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDAHAMA WERENG COKLAT DI 24 LOKASI PENGAMATAN
Lokasi
% Luas Rata-rata populasi per rumpunVarietas Tan. Muda Pop. Pop. Pop.
Peka <30 hst WBC G0 WBC G1 WBC G2X1 X2 X3 X4 X5
1 17 1.8 18 75 1802 15 1.3 14 60 1453 12.5 0.8 10 50 1004 12 0.25 9 25 755 2.5 0.35 0.2 1 306 2 0.4 0.6 1.5 487 2 0.2 0.6 5 378 0 0 0 0.5 239 0 0 0 0 0
10 0 0 0 0 5011 5 0.3 0.2 21 5812 10 1.8 7 25 10013 15 1.8 10 50 16014 14 1.45 12 60 15015 12.5 1 15 60 12016 8 0.75 3 5 2017 1 0.3 4 25 3018 1.5 0.48 0.15 5 4519 2 0.37 0.2 10 1020 0 0.23 0.6 10 021 0 0 0 0 022 0 0.5 0 18 7023 1.7 0.58 0.3 15 8024 5 0.2 0.7 30 75
Rata-rata 5.813043478 0.637391304 4.558695652 22.69565217 66.56521739Skewn 0.598691005 0.966278712 1.007722024 0.904239185 0.668934987
CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDA
KLTS Tahap 5 : Analsis multiregresi antara X1, X2, X4 dengan Y WBC (ha)
akhir musim SUMMARY OUTPUT
Y220 Regression Statistics
200 Multiple R 0.963435
125 R Square 0.928207
100 Adjusted R 0.917438
10 Standard E 22.09021
25 Observatio 24
5015 ANOVA
0 df SS MS F Significance F
10 Regression 3 126181.1 42060.36 86.19329 1.301255E-11
100 Residual 20 9759.544 487.9772
150 Total 23 135940.6
200200 CoefficientsStandard Error t Stat P-value Lower 95%
150 Intercept -5.413524 6.694334 -0.808673 0.428219 -19.37765361
50 %VarPeka X Variable 6.349087 1.913962 3.317248 0.003438 2.3566335433
10 %TanMud X Variable 40.291 14.18033 2.84133 0.010089 10.711360087
5 G1 X Variable 0.680402 0.430333 1.581106 0.12954 -0.2172566
000
30 RESIDUAL OUTPUT PROBABILITY OUTPUT
6015 ObservationPredicted Y ResidualsStandard Residuals Percentile
74.34782609 1 226.0749 -6.074912 -0.29491 2.0833333333
0.728665375 2 183.0252 16.97479 0.82405 6.253 140.203 -15.20297 -0.738036 10.4166666674 97.85832 2.14168 0.103969 14.5833333335 25.24145 -15.24145 -0.739904 18.756 24.42165 0.578347 0.028076 22.9166666677 18.74486 31.25514 1.517297 27.0833333338 -5.073323 20.07332 0.97447 31.259 -5.413524 5.413524 0.262802 35.416666667
10 -5.413524 15.41352 0.748258 39.58333333311 52.70765 47.29235 2.295831 43.7512 147.6112 2.388801 0.115966 47.91666666713 196.3667 3.633314 0.176381 52.08333333314 182.7198 17.28023 0.838878 56.2515 155.0652 -5.065189 -0.245892 60.41666666716 78.99943 -28.99943 -1.407792 64.58333333317 30.03292 -20.03292 -0.972508 68.75
18 26.8518 -21.8518 -1.060807 72.91666666719 28.99634 -28.99634 -1.407642 77.08333333320 10.65743 -10.65743 -0.51737 81.2521 -5.413524 5.413524 0.262802 85.41666666722 26.97921 3.020785 0.146646 89.58333333323 38.95474 21.04526 1.021653 93.7524 54.80217 -39.80217 -1.932217 97.916666667
Tahap 5 : Analsis multiregresi antara X1, X2, X4 dengan Y
Upper 95%Lower 95.0%Upper 95.0%
8.550605 -19.37765 8.550605
10.34154 2.356634 10.34154
69.87064 10.71136 69.87064
1.578061 -0.217257 1.578061
PROBABILITY OUTPUT
Y
0
0005
10101015152530505060
100100
0 2 4 6 8 10 12 14 16 18
-60-40-20
0204060
X Variable 1 Residual Plot
X Variable 1
Res
idu
als
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
-60-40-20
0204060
X Variable 2 Residual Plot
X Variable 2
Res
idu
als
0 2 4 6 8 10 12 14 16 18 20
-60-40-20
0204060
X Variable 3 Residual Plot
X Variable 3
Res
idu
als
0 2 4 6 8 10 12 14 16 18-500
50100150200250
X Variable 1 Line Fit Plot
Y
Predicted Y
X Variable 1Y
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2-100
0
100
200
300
X Variable 2 Line Fit Plot
Y
Predicted Y
X Variable 2
Y
0 2 4 6 8 10 12 14 16 18 20-100
0
100
200
300
X Variable 3 Line Fit Plot
Y
Predicted Y
X Variable 3
Y
0 20 40 60 80 100 1200
50100150200250
Normal Probability Plot
Sample Percentile
Y
125150150200200200220
0 2 4 6 8 10 12 14 16 18
-60-40-20
0204060
X Variable 1 Residual Plot
X Variable 1
Res
idu
als
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
-60-40-20
0204060
X Variable 2 Residual Plot
X Variable 2
Res
idu
als
0 2 4 6 8 10 12 14 16 18 20
-60-40-20
0204060
X Variable 3 Residual Plot
X Variable 3
Res
idu
als
0 2 4 6 8 10 12 14 16 18-500
50100150200250
X Variable 1 Line Fit Plot
Y
Predicted Y
X Variable 1
Y
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2-100
0
100
200
300
X Variable 2 Line Fit Plot
Y
Predicted Y
X Variable 2
Y
0 2 4 6 8 10 12 14 16 18 20-100
0
100
200
300
X Variable 3 Line Fit Plot
Y
Predicted Y
X Variable 3
Y
0 20 40 60 80 100 1200
50100150200250
Normal Probability Plot
Sample Percentile
Y
CONTOH DATA SIMULASI ANALISIS PERAMALAN MODEL LINEAR BERGANDAHAMA WERENG COKLAT DI 24 LOKASI PENGAMATAN
Lokasi
% Luas Rata-rata populasi per rumpunVarietas Tan. Muda Pop. Pop. Pop.
Peka <30 hst WBC G0 WBC G1 WBC G2X1 X2 X3 X4 X5
1 17 1.8 18 75 1802 15 1.3 14 60 1453 12.5 0.8 10 50 1004 12 0.25 9 25 755 2.5 0.35 0.2 1 306 2 0.4 0.6 1.5 487 2 0.2 0.6 5 378 0 0 0 0.5 239 0 0 0 0 0
10 0 0 0 0 5011 5 0.3 0.2 21 5812 10 1.8 7 25 10013 15 1.8 10 50 16014 14 1.45 12 60 15015 12.5 1 15 60 12016 8 0.75 3 5 2017 1 0.3 4 25 3018 1.5 0.48 0.15 5 4519 2 0.37 0.2 10 1020 0 0.23 0.6 10 021 0 0 0 0 022 0 0.5 0 18 7023 1.7 0.58 0.3 15 8024 5 0.2 0.7 30 75
Rata-rata 5.8130434783 0.6373913043 4.5586956522 22.695652174 66.565217391Skewn 0.5986910055 0.9662787117 1.0077220236 0.9042391848 0.6689349873
KLTS Tahap 6 : Analisis Multiregresi antara X1, X2, X5 dengan Y
WBC (ha)akhir musim SUMMARY OUTPUT
Y220 Regression Statistics
200 Multiple R 0.971077
125 R Square 0.94299
100 Adjusted R 0.934439
10 Standard E 19.68491
25 Observatio 24
5015 ANOVA
0 df SS MS F Significance F
10 Regression 3 128190.7 42730.24 110.2728 1.306583E-12
100 Residual 20 7749.915 387.4957
150 Total 23 135940.6
200200 CoefficientsStandard Error t Stat P-value Lower 95%
150 Intercept -12.64701 6.629857 -1.907584 0.070909 -26.47664568
50 %VarPeka X Variable 6.007107 1.495001 4.018129 0.000674 2.8885906984
10 %TanMud X Variable 24.61438 14.13804 1.741004 0.097046 -4.877043544
5 G2 X Variable 0.516546 0.178926 2.886926 0.009116 0.1433131336
000
30 RESIDUAL OUTPUT PROBABILITY OUTPUT
6015 ObservationPredicted Y ResidualsStandard Residuals Percentile
74.347826087 1 226.758 -6.757969 -0.368156 2.0833333333
0.7286653753 2 184.3575 15.64254 0.852163 6.253 133.7879 -8.787928 -0.478742 10.4166666674 104.3328 -4.332816 -0.23604 14.5833333335 26.48217 -16.48217 -0.897904 18.756 34.00716 -9.007162 -0.490686 22.9166666677 23.40228 26.59772 1.448972 27.0833333338 -0.766454 15.76645 0.858914 31.259 -12.64701 12.64701 0.688975 35.416666667
10 13.18029 -3.180289 -0.173254 39.58333333311 54.7325 45.2675 2.46605 43.7512 143.3845 6.615461 0.360392 47.91666666713 204.4128 -4.412835 -0.240399 52.08333333314 184.6252 15.37476 0.837575 56.2515 149.0417 0.958276 0.052204 60.41666666716 64.20155 -14.20155 -0.773662 64.58333333317 16.24079 -6.240789 -0.339981 68.75
18 31.42312 -26.42312 -1.43946 72.91666666719 13.63998 -13.63998 -0.743069 77.08333333320 -6.985705 6.985705 0.380562 81.2521 -12.64701 12.64701 0.688975 85.41666666722 35.8184 -5.818399 -0.316971 89.58333333323 53.16509 6.834909 0.372347 93.7524 61.05235 -46.05235 -2.508807 97.916666667
Upper 95%Lower 95.0%Upper 95.0%
1.182621 -26.47665 1.182621
9.125623 2.888591 9.125623
54.1058 -4.877044 54.1058
0.889779 0.143313 0.889779
PROBABILITY OUTPUT
Y
0
0005
10101015152530505060
100100
0 2 4 6 8 10 12 14 16 18
-60-40-20
0204060
X Variable 1 Residual Plot
X Variable 1
Res
idu
als
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
-60-40-20
0204060
X Variable 2 Residual Plot
X Variable 2
Res
idu
als
0 2 4 6 8 10 12 14 16 18 20
-60-40-20
0204060
X Variable 3 Residual Plot
X Variable 3
Res
idu
als
0 2 4 6 8 10 12 14 16 18-500
50100150200250
X Variable 1 Line Fit Plot
Y
Predicted Y
X Variable 1Y
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2-100
0
100
200
300
X Variable 2 Line Fit Plot
Y
Predicted Y
X Variable 2
Y
0 2 4 6 8 10 12 14 16 18 20-100
0
100
200
300
X Variable 3 Line Fit Plot
Y
Predicted Y
X Variable 3
Y
0 20 40 60 80 100 1200
50100150200250
Normal Probability Plot
Sample Percentile
Y
125150150200200200220
0 2 4 6 8 10 12 14 16 18
-60-40-20
0204060
X Variable 1 Residual Plot
X Variable 1
Res
idu
als
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
-60-40-20
0204060
X Variable 2 Residual Plot
X Variable 2
Res
idu
als
0 2 4 6 8 10 12 14 16 18 20
-60-40-20
0204060
X Variable 3 Residual Plot
X Variable 3
Res
idu
als
0 2 4 6 8 10 12 14 16 18-500
50100150200250
X Variable 1 Line Fit Plot
Y
Predicted Y
X Variable 1
Y
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2-100
0
100
200
300
X Variable 2 Line Fit Plot
Y
Predicted Y
X Variable 2
Y
0 2 4 6 8 10 12 14 16 18 20-100
0
100
200
300
X Variable 3 Line Fit Plot
Y
Predicted Y
X Variable 3
Y
0 20 40 60 80 100 1200
50100150200250
Normal Probability Plot
Sample Percentile
Y
KESIMPULAN AHASIL ANALISIS MULTI REGRESI
SUMMARY OUTPUT SUMMARY OUTPUT
Regression Statistics Regression StatisticsMultiple R 0.960552 Multiple RR Square 0.9226601 R SquareAdjusted R Square 0.9110591 Adjusted R SquareStandard Error 22.927756 Standard ErrorObservations 24 Observations
Coefficients CoefficientsIntercept -2.0248879 Intercept
%VarPeka X Variable 1 6.554926 %VarPeka X Variable 1%TanMud X Variable 2 42.854424 %TanMud X Variable 2G0 X Variable 3 2.1564409 G1 X Variable 3
Significance F Significance F2.73E-11 1.30E-11
Y = 6,555 X1 + 42,854 X2 + 2,156 X3 - 2, 025 Y = 6,349 X1 + 40,291 X2 + 0,6804 X4 - 5,4135
R = 0,9606 R = 0,9634
Sig, F = 2.73163726431331E-11 Sig, F = 1.30125495325999E-11R2 = 0,9227 R2 = 0,9282
SUMMARY OUTPUT
Regression Statistics Regression Statistics0.9634352 Multiple R 0.9710770.9282073 R Square 0.94299040.9174384 Adjusted R Square 0.93443922.090206 Standard Error 19.684911
24 Observations 24Coefficients Coefficients-5.4135244 Intercept -12.6470126.3490867 %VarPeka X Variable 1 6.007106840.291002 %TanMud X Variable 2 24.6143780.6804021 G2 X Variable 3 0.516546
Significance F1.31E-12
Y = 6,349 X1 + 40,291 X2 + 0,6804 X4 - 5,4135 Y = 6,007 X1 + 24,614 X2 + 0,5165 X5 - 12,647
R = 0,971
Sig, F = 1.30125495325999E-11 Sig, F = 1.30658303353243E-12R2 = 0,943
