uji ranking - repository.unika.ac.idrepository.unika.ac.id/6921/8/05.70.0009 elfira widyastuti -...
TRANSCRIPT
1
7. LAMPIRAN Lampiran 1. Kuisioner Uji Sensoris
Uji Ranking
Nama : Tanggal :
Usia :
Jenis Kelamin : L / P
Produk : Guava leather
Kriteria : Warna
Instruksi :
Di hadapan Anda terdapat 3 sampel guava leather. Lakukan pengujian terhadap tingkat
kesukaan warna sampel guava leather. Kemudian bandingkan tingkat kesukaan warna
sampel guava leather dan ranking tingkat kesukaan warna sampel tersebut (ranking
tidak boleh sama). Urutkan sampel dari yang paling kurang Anda sukai (= 1) hingga
sampel yang paling Anda sukai (= 3), dengan mengisikan kode sampel pada kolom di
bawah ini :
Kode Sampel Ranking
A
B
C
2
Uji Ranking
Nama : Tanggal :
Usia :
Jenis Kelamin : L / P
Produk : Guava leather
Kriteria : Hardness
Instruksi :
Di hadapan Anda terdapat 3 sampel guava leather. Lakukan pengujian terhadap tingkat
kesukaan hardness sampel guava leather. Letakkan sampel guava leather diantara gigi
geraham kemudian gigitlah dan ukur kekuatan yang dibutuhkan untuk menggigit
sampel. Kemudian bandingkan tingkat kesukaan hardness sampel guava leather dan
ranking tingkat kesukaan hardness sampel tersebut (rangking tidak boleh sama).
Urutkan sampel dari yang paling kurang Anda sukai (= 1) hingga sampel yang paling
Anda sukai (= 3), dengan mengisikan kode sampel pada kolom di bawah ini :
Kode Sampel Ranking
A
B
C
3
Uji Ranking
Nama : Tanggal :
Usia :
Jenis Kelamin : L / P
Produk : Guava leather
Kriteria : Adhesiveness
Instruksi :
Di hadapan Anda terdapat 3 sampel guava leather. Lakukan pengujian terhadap tingkat
kesukaan adhesiveness sampel guava leather. Letakkan sampel guava leather diantara
bibir kemudian tekan sampel dengan menggunakan bibir dan ukur kekuatan yang
dibutuhkan untuk memindahkan sampel. Kemudian bandingkan tingkat kesukaan
adhesiveness sampel guava leather dan ranking tingkat kesukaan adhesiveness sampel
tersebut (rangking tidak boleh sama). Urutkan sampel dari yang paling kurang Anda
sukai (= 1) hingga sampel yang paling Anda sukai (= 3), dengan mengisikan kode
sampel pada kolom di bawah ini :
Kode Sampel Ranking
A
B
C
4
Uji Ranking
Nama : Tanggal :
Usia :
Jenis Kelamin : L / P
Produk : Guava leather
Kriteria : Cohesiveness
Instruksi :
Di hadapan Anda terdapat 3 sampel guava leather. Lakukan pengujian terhadap tingkat
kesukaan cohesiveness sampel guava leather. Letakkan sampel guava leather diantara
gigi geraham kemudian tekan dan ukur kekuatan yang yang ada pada sampel sampai
sampel benar-benar hancur. Kemudian bandingkan tingkat kesukaan cohesiveness
sampel guava leather dan ranking tingkat kesukaan cohesiveness sampel tersebut
(rangking tidak boleh sama). Urutkan sampel dari yang paling kurang Anda sukai (= 1)
hingga sampel yang paling Anda sukai (= 3), dengan mengisikan kode sampel pada
kolom di bawah ini :
Kode Sampel Ranking
A
B
C
5
Uji Ranking
Nama : Tanggal :
Usia :
Jenis Kelamin : L / P
Produk : Guava leather
Kriteria : Springiness
Instruksi :
Di hadapan Anda terdapat 3 sampel guava leather. Lakukan pengujian terhadap tingkat
kesukaan springiness sampel guava leather. Letakkan sampel guava leather diantara
gigi geraham kemudian tekan dan ukur seberapa besar sampel bisa kembali ke bentuk
semula setelah ditekan. Kemudian bandingkan tingkat kesukaan springiness sampel
guava leather dan ranking tingkat kesukaan springiness sampel tersebut (rangking tidak
boleh sama). Urutkan sampel dari yang paling kurang Anda sukai (= 1) hingga sampel
yang paling Anda sukai (= 3), dengan mengisikan kode sampel pada kolom di bawah ini
:
Kode Sampel Ranking
A
B
C
6
Uji Ranking
Nama : Tanggal :
Usia :
Jenis Kelamin : L / P
Produk : Guava leather
Kriteria : Chewiness
Instruksi :
Di hadapan Anda terdapat 3 sampel guava leather. Lakukan pengujian terhadap tingkat
kesukaan hardness sampel guava leather. Letakkan sampel guava leather di dalam
mulut kemudian mulailah untuk mengunyah sampel perlahan, kemudian ukurlah
banyaknya pengunyahan yang dibutuhkan sampel hingga sampel menjadi siap untuk
ditelan. Kemudian bandingkan tingkat kesukaan chewiness sampel guava leather dan
ranking tingkat kesukaan chewiness sampel tersebut (rangking tidak boleh sama).
Urutkan sampel dari yang paling kurang Anda sukai (= 1) hingga sampel yang paling
Anda sukai (= 3), dengan mengisikan kode sampel pada kolom di bawah ini :
Kode Sampel Ranking
A
B
C
7
Uji Ranking
Nama : Tanggal :
Usia :
Jenis Kelamin : L / P
Produk : Guava leather
Kriteria : Overall
Instruksi :
Di hadapan Anda terdapat 3 sampel guava leather. Lakukan pengujian terhadap tingkat
kesukaan overall sampel guava leather dengan cara mencicipi sampel secara berurutan
dari kiri ke kanan. Kemudian bandingkan tingkat kesukaan overall sampel guava
leather dan ranking tingkat kesukaan overall sampel tersebut (rangking tidak boleh
sama). Urutkan sampel dari yang paling kurang Anda sukai (= 1) hingga sampel yang
paling Anda sukai (= 3), dengan mengisikan kode sampel pada kolom di bawah ini :
Kode Sampel Ranking
A
B
C
8
Lampiran 2. Deskriptif Statistik Kadar Air Guava leather Descriptive Statistics Dependent Variable: k_air
tebal suhu Mean Std. Deviation N suhu 60 16.9467 .31392 6suhu 70 15.7467 1.41627 6suhu 80 14.0600 1.92265 6
tebal 5 mm
Total 15.5844 1.78623 18suhu 60 17.4867 .79661 6suhu 70 16.3400 1.26103 6suhu 80 15.0833 .81220 6
tebal 7 mm
Total 16.3033 1.36689 18suhu 60 20.0450 .72426 6suhu 70 18.3917 .95926 6suhu 80 17.6783 1.39978 6
tebal 9 mm
Total 18.7050 1.42885 18suhu 60 18.1594 1.51776 18suhu 70 16.8261 1.63951 18suhu 80 15.6072 2.07684 18
Total
Total 16.8643 2.02273 54 Lampiran 3. Tabel Pos Hoc Kadar Air Guava leather terhadap Perbedaan Suhu
Pengeringan k_air Duncan
N Subset suhu 1 2 3 1 suhu 80 18 15.6072 suhu 70 18 16.8261 suhu 60 18 18.1594Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 1.343. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
9
Lampiran 4. Tabel Pos Hoc Kadar Air Guava leather terhadap Perbedaan Ketebalan Guava Puree
k_air Duncan
N Subset tebal 1 2 1 tebal 5 mm 18 15.5844 tebal 7 mm 18 16.3033 tebal 9 mm 18 18.7050Sig. .069 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 1.343. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05. Lampiran 5. Deskriptif Statistik Aktivitas Air Guava leather Descriptive Statistics Dependent Variable: aw
tebal suhu Mean Std. Deviation N suhu 60 .6283 .02787 6suhu 70 .5583 .07935 6suhu 80 .5450 .03017 6
tebal 5 mm
Total .5772 .06134 18suhu 60 .6317 .03189 6suhu 70 .5950 .05683 6suhu 80 .5467 .05922 6
tebal 7 mm
Total .5911 .05969 18suhu 60 .6900 .01549 6suhu 70 .6517 .03488 6suhu 80 .6333 .04227 6
tebal 9 mm
Total .6583 .03930 18suhu 60 .6500 .03804 18suhu 70 .6017 .06871 18suhu 80 .5750 .06022 18
Total
Total .6089 .06421 54
10
Lampiran 6. Tabel Pos Hoc Aktivitas Air Guava leather terhadap Perbedaan Suhu
Pengeringan aw Duncan
N Subset suhu 1 2 1 suhu 80 18 .5750 suhu 70 18 .6017 suhu 60 18 .6500Sig. .088 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .002. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05. Lampiran 7. Tabel Pos Hoc Aktivitas Air Guava leather terhadap Perbedaan
Ketebalan Guava Puree aw Duncan
N Subset tebal 1 2 1 tebal 5 mm 18 .5772 tebal 7 mm 18 .5911 tebal 9 mm 18 .6583Sig. .369 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .002. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
11
Lampiran 8. Deskriptif Statistik Vitamin C Guava leather Descriptive Statistics Dependent Variable: vit_c
tebal suhu Mean Std. Deviation N suhu 60 366.0633 29.90870 6suhu 70 344.4250 20.18950 6suhu 80 292.1583 23.26288 6
tebal 5 mm
Total 334.2156 39.51208 18suhu 60 355.4650 31.38398 6suhu 70 329.6483 12.06227 6suhu 80 276.3633 28.40173 6
tebal 7 mm
Total 320.4922 41.45251 18suhu 60 341.1750 10.93387 6suhu 70 319.9783 27.27078 6suhu 80 272.9450 12.41281 6
tebal 9 mm
Total 311.3661 34.05890 18suhu 60 354.2344 26.42090 18suhu 70 331.3506 22.10010 18suhu 80 280.4889 22.71321 18
Total
Total 322.0246 38.90826 54 Lampiran 9. Tabel Pos Hoc Vitamin C Guava leather terhadap Perbedaan Suhu
Pengeringan vit_c Duncan
N Subset suhu 1 2 3 1 suhu 80 18 280.4889 suhu 70 18 331.3506 suhu 60 18 354.2344Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 533.082. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
12
Lampiran 10. Tabel Pos Hoc Vitamin C Guava leather terhadap Perbedaan
Ketebalan Guava Puree vit_c Duncan
N Subset tebal 1 2 1 tebal 9 mm 18 311.3661 tebal 7 mm 18 320.4922 320.4922tebal 5 mm 18 334.2156Sig. .242 .081
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 533.082. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05. Lampiran 11. Deskriptif Statistik hardness Guava leather Descriptive Statistics Dependent Variable: hardness
tebal suhu Mean Std. Deviation N suhu 60 61.4967 2.34504 6suhu 70 73.3350 4.14718 6suhu 80 83.0367 3.15584 6
tebal 5 mm
Total 72.6228 9.57868 18suhu 60 34.5550 3.78987 6suhu 70 55.4733 1.44692 6suhu 80 66.6017 3.68363 6
tebal 7 mm
Total 52.2100 13.98937 18suhu 60 19.9217 2.52849 6suhu 70 36.9767 1.17098 6suhu 80 44.8017 3.71453 6
tebal 9 mm
Total 33.9000 10.98139 18suhu 60 38.6578 17.93487 18suhu 70 55.2617 15.47200 18suhu 80 64.8133 16.45164 18
Total
Total 52.9109 19.64069 54
13
Lampiran 12. Tabel Pos Hoc hardness Guava leather terhadap Perbedaan Suhu Pengeringan
hardness Duncan
N Subset suhu 1 2 3 1 suhu 60 18 38.6578 suhu 70 18 55.2617 suhu 80 18 64.8133Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 9.361. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05. Lampiran 13. Tabel Pos Hoc hardness Guava leather terhadap Perbedaan
Ketebalan Guava Puree hardness Duncan
N Subset tebal 1 2 3 1 tebal 9 mm 18 33.9000 tebal 7 mm 18 52.2100 tebal 5 mm 18 72.6228Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 9.361. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
14
Lampiran 14. Deskriptif Statistik adhesiveness Guava leather Descriptive Statistics Dependent Variable: adhesiv
tebal suhu Mean Std. Deviation N suhu 60 .0035 .00096 6suhu 70 .0024 .00098 6suhu 80 .0014 .00041 6
tebal 5 mm
Total .0024 .00117 18suhu 60 .0221 .00326 6suhu 70 .0166 .00078 6suhu 80 .0097 .00343 6
tebal 7 mm
Total .0161 .00582 18suhu 60 .0412 .00473 6suhu 70 .0308 .00211 6suhu 80 .0229 .00203 6
tebal 9 mm
Total .0316 .00829 18suhu 60 .0223 .01614 18suhu 70 .0166 .01199 18suhu 80 .0113 .00935 18
Total
Total .0167 .01334 54 Lampiran 15. Tabel Pos Hoc adhesiveness Guava leather terhadap Perbedaan Suhu
Pengeringan adhesiv Duncan
N Subset suhu 1 2 3 1 suhu 80 18 .0113 suhu 70 18 .0166 suhu 60 18 .0223Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 6.23E-006. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
15
Lampiran 16. Tabel Pos Hoc adhesiveness Guava leather terhadap Perbedaan Ketebalan Guava Puree
adhesiv Duncan
N Subset tebal 1 2 3 1 tebal 5 mm 18 .0024 tebal 7 mm 18 .0161 tebal 9 mm 18 .0316Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 6.23E-006. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05. Lampiran 17. Deskriptif Statistik cohesiveness Guava leather Descriptive Statistics Dependent Variable: cohesive
tebal suhu Mean Std. Deviation N suhu 60 .0257 .00593 6suhu 70 .0032 .00100 6suhu 80 .0033 .00082 6
tebal 5 mm
Total .0108 .01137 18suhu 60 .0275 .00455 6suhu 70 .0082 .00096 6suhu 80 .0041 .00094 6
tebal 7 mm
Total .0133 .01079 18suhu 60 .0335 .00131 6suhu 70 .0126 .00203 6suhu 80 .0066 .00113 6
tebal 9 mm
Total .0176 .01196 18suhu 60 .0289 .00537 18suhu 70 .0080 .00414 18suhu 80 .0047 .00172 18
Total
Total .0139 .01152 54
16
Lampiran 18. Tabel Pos Hoc cohesiveness Guava leather terhadap Perbedaan Suhu Pengeringan
cohesive Duncan
N Subset suhu 1 2 3 1 suhu 80 18 .0047 suhu 70 18 .0080 suhu 60 18 .0289Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 7.39E-006. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05. Lampiran 19. Tabel Pos Hoc cohesiveness Guava leather terhadap Perbedaan
Ketebalan Guava Puree cohesive Duncan
N Subset tebal 1 2 3 1 tebal 5 mm 18 .0108 tebal 7 mm 18 .0133 tebal 9 mm 18 .0176Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 7.39E-006. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
17
Lampiran 20. Deskriptif Statistik chewiness Guava leather Descriptive Statistics Dependent Variable: chewi
tebal suhu Mean Std. Deviation N suhu 60 .0299 .00623 6suhu 70 .0811 .00722 6suhu 80 .1690 .06175 6
tebal 5 mm
Total .0933 .06811 18suhu 60 .0036 .00070 6suhu 70 .0086 .00099 6suhu 80 .0202 .00538 6
tebal 7 mm
Total .0108 .00775 18suhu 60 .0026 .00064 6suhu 70 .0034 .00071 6suhu 80 .0078 .00095 6
tebal 9 mm
Total .0046 .00249 18suhu 60 .0120 .01348 18suhu 70 .0310 .03669 18suhu 80 .0657 .08251 18
Total
Total .0362 .05636 54 Lampiran 21. Tabel Pos Hoc chewiness Guava leather terhadap Perbedaan Suhu
Pengeringan chewi Duncan
N Subset suhu 1 2 3 1 suhu 60 18 .0120 suhu 70 18 .0310 suhu 80 18 .0657Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .000. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
18
Lampiran 22. Tabel Pos Hoc chewiness Guava leather terhadap Perbedaan Ketebalan Guava Puree
chewi Duncan
N Subset tebal 1 2 1 tebal 9 mm 18 .0046 tebal 7 mm 18 .0108 tebal 5 mm 18 .0933Sig. .379 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .000. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05. Lampiran 23. Deskriptif Statistik springiness Guava leather Descriptive Statistics Dependent Variable: springi
tebal suhu Mean Std. Deviation N suhu 60 .4537 .02170 6suhu 70 .6015 .21176 6suhu 80 1.0666 .08959 6
tebal 5 mm
Total .7073 .29648 18suhu 60 .1163 .01357 6suhu 70 .2782 .10109 6suhu 80 .4475 .39877 6
tebal 7 mm
Total .2807 .26305 18suhu 60 .0488 .01410 6suhu 70 .1495 .00842 6suhu 80 .1799 .01304 6
tebal 9 mm
Total .1261 .05876 18suhu 60 .2063 .18294 18suhu 70 .3431 .23345 18suhu 80 .5647 .44181 18
Total
Total .3713 .33622 54
19
Lampiran 24. Tabel Pos Hoc springiness Guava leather terhadap Perbedaan Suhu Pengeringan
springi Duncan
N Subset suhu 1 2 3 1 suhu 60 18 .2063 suhu 70 18 .3431 suhu 80 18 .5647Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .025. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05. Lampiran 25. Tabel Pos Hoc springiness Guava leather terhadap Perbedaan
Ketebalan Guava Puree springi Duncan
N Subset tebal 1 2 3 1 tebal 9 mm 18 .1261 tebal 7 mm 18 .2807 tebal 5 mm 18 .7073Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .025. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
20
Lampiran 26. Deskriptif Statistik lightness (L) Guava leather Descriptive Statistics Dependent Variable: L
tebal suhu Mean Std. Deviation N suhu 60 38.2100 .83153 6suhu 70 38.1883 .48852 6suhu 80 37.9650 .62099 6
tebal 5 mm
Total 38.1211 .63243 18suhu 60 37.8000 .34911 6suhu 70 36.5700 .65348 6suhu 80 35.4733 .75796 6
tebal 7 mm
Total 36.6144 1.13436 18suhu 60 34.2200 1.02257 6suhu 70 34.1883 .97907 6suhu 80 32.7733 .92567 6
tebal 9 mm
Total 33.7272 1.15039 18suhu 60 36.7433 1.98678 18suhu 70 36.3156 1.82634 18suhu 80 35.4039 2.30075 18
Total
Total 36.1543 2.08610 54 Lampiran 27. Tabel Pos Hoc lightness (L) Guava leather terhadap Perbedaan Suhu
Pengeringan L Duncan
N Subset suhu 1 2 1 suhu 80 18 35.4039 suhu 70 18 36.3156suhu 60 18 36.7433Sig. 1.000 .101
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .589. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
21
Lampiran 28. Tabel Pos Hoc lightness (L) Guava leather terhadap Perbedaan Ketebalan Guava Puree
L Duncan
N Subset tebal 1 2 3 1 tebal 9 mm 18 33.7272 tebal 7 mm 18 36.6144 tebal 5 mm 18 38.1211Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .589. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05. Lampiran 29. Deskriptif Statistik redness (a) Guava leather Descriptive Statistics Dependent Variable: a
tebal suhu Mean Std. Deviation N suhu 60 21.1883 .90993 6suhu 70 21.8217 .73311 6suhu 80 22.2183 .81996 6
tebal 5 mm
Total 21.7428 .88874 18suhu 60 23.8883 .89821 6suhu 70 25.2917 .63066 6suhu 80 25.6117 .88400 6
tebal 7 mm
Total 24.9306 1.08501 18suhu 60 27.6033 .73451 6suhu 70 28.3833 .88746 6suhu 80 28.6917 .61895 6
tebal 9 mm
Total 28.2261 .85153 18suhu 60 24.2267 2.82175 18suhu 70 25.1656 2.84836 18suhu 80 25.5072 2.81795 18
Total
Total 24.9665 2.82878 54
22
Lampiran 30. Tabel Pos Hoc redness (a) Guava leather terhadap Perbedaan Suhu Pengeringan
a Duncan
N Subset suhu 1 2 1 suhu 60 18 24.2267 suhu 70 18 25.1656suhu 80 18 25.5072Sig. 1.000 .206
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .637. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05. Lampiran 31. Tabel Pos Hoc redness (a) Guava leather terhadap Perbedaan
Ketebalan Guava Puree a Duncan
N Subset tebal 1 2 3 1 tebal 5 mm 18 21.7428 tebal 7 mm 18 24.9306 tebal 9 mm 18 28.2261Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .637. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
23
Lampiran 32. Deskriptif Statistik yellowness (b) Guava leather Descriptive Statistics Dependent Variable: b
tebal suhu Mean Std. Deviation N suhu 60 6.4617 .34132 6suhu 70 6.4550 .10015 6suhu 80 6.3250 .41746 6
tebal 5 mm
Total 6.4139 .30440 18suhu 60 5.7417 .41778 6suhu 70 5.4850 .23407 6suhu 80 5.3917 .33677 6
tebal 7 mm
Total 5.5394 .35213 18suhu 60 4.9317 .39555 6suhu 70 4.6183 .15791 6suhu 80 4.4967 .18843 6
tebal 9 mm
Total 4.6822 .31519 18suhu 60 5.7117 .73837 18suhu 70 5.5194 .78887 18suhu 80 5.4044 .82768 18
Total
Total 5.5452 .78140 54 Lampiran 33. Tabel Pos Hoc yellowness (b) Guava leather terhadap Perbedaan
Suhu Pengeringan b Duncan
N Subset suhu 1 2 1 suhu 80 18 5.4044 suhu 70 18 5.5194 5.5194suhu 60 18 5.7117Sig. .270 .069
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .096. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
24
Lampiran 34. Tabel Pos Hoc yellowness (b) Guava leather terhadap Perbedaan Ketebalan Guava Puree
b Duncan
N Subset tebal 1 2 3 1 tebal 9 mm 18 4.6822 tebal 7 mm 18 5.5394 tebal 5 mm 18 6.4139Sig. 1.000 1.000 1.000
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = .096. a Uses Harmonic Mean Sample Size = 18.000. b Alpha = .05.
Lampiran 35. SPSS Uji Sensoris Test Statistics(a,b) WARNA HARDNES ADHESIV COHESIV CHEWI SPRINGI OVERALL Chi-Square .238 8.761 1.588 19.370 31.290 17.344 5.424df 2 2 2 2 2 2 2Asymp. Sig. .888 .013 .452 .000 .000 .000 .066
a Kruskal Wallis Test b Grouping Variable: TEBAL Tebal 5 mm dan Tebal 7 mm Test Statistics(a) HARDNES COHESIV CHEWI SPRINGI Mann-Whitney U 971.500 802.500 702.500 808.000Wilcoxon W 2246.500 2077.500 1977.500 2083.000Z -2.048 -3.300 -4.053 -3.255Asymp. Sig. (2-tailed) .041 .001 .000 .001
a Grouping Variable: TEBAL Tebal 7 mm dan Tebal 9 mm Test Statistics(a) HARDNES COHESIV CHEWI SPRINGI Mann-Whitney U 1071.500 1052.500 952.500 1058.000Wilcoxon W 2346.500 2327.500 2227.500 2333.000Z -1.313 -1.460 -2.215 -1.421Asymp. Sig. (2-tailed) .189 .144 .027 .155
a Grouping Variable: TEBAL
25
Tebal 5 mm dan Tebal 9 mm Test Statistics(a) HARDNES COHESIV CHEWI SPRINGI Mann-Whitney U 878.500 697.500 547.500 742.000Wilcoxon W 2153.500 1972.500 1822.500 2017.000Z -2.736 -4.056 -5.170 -3.750Asymp. Sig. (2-tailed) .006 .000 .000 .000
a Grouping Variable: TEBAL Lampiran 36. Regresi non linear untuk persamaan Arrhenius (Vitamin C) pada
Guava leather dengan ketebalan 5 mm Iteration History(b)
Residual Sum of Squares Parameter Iteration
Number(a)
A Ea 1.0 146.203 .100 .1001.1 176.521 1.108 8820.7271.2 20.715 .528 -7674.6542.0 20.715 .528 -7674.6542.1 2.404 1.565 -9542.5773.0 2.404 1.565 -9542.5773.1 .773 3.645 -8258.7604.0 .773 3.645 -8258.7604.1 .105 5.724 -8011.1135.0 .105 5.724 -8011.1135.1 .149 9.882 -6281.2035.2 .060 7.165 -7633.4456.0 .060 7.165 -7633.4456.1 .064 10.046 -6565.4936.2 .055 8.279 -7267.8707.0 .055 8.279 -7267.8707.1 .053 10.508 -6532.3298.0 .053 10.508 -6532.3298.1 .048 12.737 -6015.9199.0 .048 12.737 -6015.9199.1 .049 17.194 -5075.2569.2 .045 14.712 -5630.36810.0 .045 14.712 -5630.36810.1 .043 18.663 -4896.49911.0 .043 18.663 -4896.49911.1 .038 22.614 -4380.85512.0 .038 22.614 -4380.85512.1 .040 30.516 -3441.56712.2 .035 25.878 -4025.83813.0 .035 25.878 -4025.838
26
13.1 .034 32.405 -3334.47514.0 .034 32.405 -3334.47514.1 .030 38.932 -2838.50515.0 .030 38.932 -2838.50515.1 .032 51.986 -1934.43615.2 .028 44.247 -2500.64816.0 .028 44.247 -2500.64816.1 .026 54.877 -1840.65317.0 .026 54.877 -1840.65317.1 .023 65.507 -1359.90318.0 .023 65.507 -1359.90318.1 .025 86.768 -482.83118.2 .021 73.870 -1043.68119.0 .021 73.870 -1043.68119.1 .020 90.595 -420.15520.0 .020 90.595 -420.15520.1 .017 107.321 42.13821.0 .017 107.321 42.13821.1 .019 140.771 886.68221.2 .016 120.085 337.64522.0 .016 120.085 337.64522.1 .015 145.614 924.52923.0 .015 145.614 924.52923.1 .013 171.144 1367.43524.0 .013 171.144 1367.43524.1 .014 222.202 2177.98824.2 .011 189.961 1641.37125.0 .011 189.961 1641.37125.1 .011 227.595 2189.64726.0 .011 227.595 2189.64726.1 .009 265.229 2611.19427.0 .009 265.229 2611.19427.1 .008 302.864 2980.25328.0 .008 302.864 2980.25328.1 .008 378.132 3661.94128.2 .007 335.053 3256.77829.0 .007 335.053 3256.77829.1 .007 399.433 3789.06930.0 .007 399.433 3789.06930.1 .005 463.812 4201.48731.0 .005 463.812 4201.48731.1 .004 528.191 4563.41932.0 .004 528.191 4563.41932.1 .005 656.949 5232.65832.2 .004 574.114 4785.93633.0 .004 574.114 4785.93633.1 .004 665.960 5231.45034.0 .004 665.960 5231.45034.1 .003 757.805 5591.319
27
35.0 .003 757.805 5591.31935.1 .002 849.651 5911.72236.0 .002 849.651 5911.72236.1 .003 1033.343 6508.18036.2 .002 912.072 6101.61637.0 .002 912.072 6101.61637.1 .002 1036.912 6484.17338.0 .002 1036.912 6484.17338.1 .001 1161.753 6802.64539.0 .001 1161.753 6802.64539.1 .001 1286.593 7089.61440.0 .001 1286.593 7089.61440.1 .001 1411.434 7350.65141.0 .001 1411.434 7350.65141.1 .001 1661.115 7841.94141.2 .001 1487.430 7491.42142.0 .001 1487.430 7491.42142.1 .001 1639.422 7778.50443.0 .001 1639.422 7778.50443.1 .001 1791.414 8028.65844.0 .001 1791.414 8028.65844.1 .000 1943.406 8258.80245.0 .000 1943.406 8258.80245.1 .000 2095.398 8471.87146.0 .000 2095.398 8471.87146.1 .000 2247.391 8670.20547.0 .000 2247.391 8670.20547.1 .000 2396.688 8852.28348.0 .000 2396.688 8852.28348.1 .000 2401.753 8852.28349.0 .000 2401.753 8852.28349.1 .000 2401.759 8852.28450.0 .000 2401.759 8852.284
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 112 model evaluations and 50 derivative evaluations because the relative reduction between successive parameter estimates is at most PCON = 1.00E-008. Parameter Estimates
95% Confidence Interval Parameter Estimate Std. Error Lower Bound Upper Bound A 2401.759 1049.060 -10927.816 15731.333Ea 8852.284 1244.531 -6960.986 24665.554
28
Correlations of Parameter Estimates A Ea A 1.000 .999 Ea .999 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 65.667 2 32.834Residual .000 1 .000Uncorrected Total 65.667 3 Corrected Total .017 2
Dependent variable: t5 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .981. Lampiran 37. Regresi non linear untuk persamaan Arrhenius (Vitamin C) pada
Guava leather dengan ketebalan 7 mm Iteration History(b)
Residual Sum of Squares Parameter Iteration
Number(a) A Ea 1.0 144.551 .100 .1001.1 255.581 1.278 13786.7521.2 19.125 .514 -7936.4122.0 19.125 .514 -7936.4122.1 2.548 1.539 -9423.4063.0 2.548 1.539 -9423.4063.1 .825 3.591 -8175.4554.0 .825 3.591 -8175.4554.1 .146 5.643 -7933.7355.0 .146 5.643 -7933.7355.1 .187 9.746 -6202.6555.2 .100 7.116 -7530.4746.0 .100 7.116 -7530.4746.1 .102 10.061 -6434.2946.2 .094 8.388 -7103.9137.0 .094 8.388 -7103.9137.1 .091 10.934 -6280.3828.0 .091 10.934 -6280.3828.1 .083 13.479 -5726.7289.0 .083 13.479 -5726.7289.1 .084 18.570 -4717.9029.2 .078 15.861 -5290.25210.0 .078 15.861 -5290.252
29
10.1 .076 20.626 -4474.44511.0 .076 20.626 -4474.44511.1 .069 25.390 -3923.89812.0 .069 25.390 -3923.89812.1 .070 34.920 -2920.84512.2 .065 29.632 -3514.09213.0 .065 29.632 -3514.09213.1 .062 38.114 -2734.47314.0 .062 38.114 -2734.47314.1 .056 46.597 -2198.86315.0 .056 46.597 -2198.86315.1 .058 63.562 -1223.34015.2 .053 54.020 -1806.63716.0 .053 54.020 -1806.63716.1 .051 68.867 -1056.49317.0 .051 68.867 -1056.49317.1 .046 83.714 -533.60918.0 .046 83.714 -533.60918.1 .047 113.407 418.75418.2 .042 96.346 -161.78719.0 .042 96.346 -161.78719.1 .041 121.609 555.64320.0 .041 121.609 555.64320.1 .036 146.873 1063.80121.0 .036 146.873 1063.80121.1 .038 197.400 1989.64321.2 .033 167.806 1415.67722.0 .033 167.806 1415.67722.1 .032 209.671 2099.88623.0 .032 209.671 2099.88623.1 .028 251.536 2592.43624.0 .028 251.536 2592.43624.1 .030 335.266 3490.42424.2 .026 285.235 2923.84925.0 .026 285.235 2923.84925.1 .025 352.632 3573.41826.0 .025 352.632 3573.41826.1 .022 420.029 4048.97527.0 .022 420.029 4048.97527.1 .023 554.823 4916.87627.2 .020 472.656 4359.65028.0 .020 472.656 4359.65028.1 .019 577.910 4973.31629.0 .019 577.910 4973.31629.1 .016 683.164 5430.47530.0 .016 683.164 5430.47530.1 .018 893.673 6266.00430.2 .015 762.722 5720.00031.0 .015 762.722 5720.000
30
31.1 .014 921.836 6296.29732.0 .014 921.836 6296.29732.1 .012 1080.951 6733.44133.0 .012 1080.951 6733.44133.1 .013 1399.180 7533.91833.2 .010 1197.085 7001.36634.0 .010 1197.085 7001.36634.1 .010 1429.353 7538.69935.0 .010 1429.353 7538.69935.1 .008 1661.620 7954.01436.0 .008 1661.620 7954.01436.1 .007 1893.888 8318.21137.0 .007 1893.888 8318.21137.1 .008 2358.423 8991.40737.2 .006 2089.415 8586.81038.0 .006 2089.415 8586.81038.1 .006 2480.469 9105.71839.0 .006 2480.469 9105.71839.1 .005 2871.523 9510.36440.0 .005 2871.523 9510.36440.1 .004 3262.577 9866.21041.0 .004 3262.577 9866.21041.1 .005 4044.686 10524.81141.2 .004 3536.449 10081.08342.0 .004 3536.449 10081.08342.1 .003 4084.192 10512.76143.0 .003 4084.192 10512.76143.1 .003 4631.936 10863.77544.0 .003 4631.936 10863.77544.1 .002 5179.679 11177.08245.0 .002 5179.679 11177.08245.1 .003 6275.165 11761.05145.2 .002 5543.495 11358.68346.0 .002 5543.495 11358.68346.1 .002 6271.127 11725.85547.0 .002 6271.127 11725.85547.1 .001 6998.760 12033.77848.0 .001 6998.760 12033.77848.1 .001 7726.392 12312.11349.0 .001 7726.392 12312.11349.1 .001 8454.024 12565.96350.0 .001 8454.024 12565.96350.1 .001 9909.289 13044.40550.2 .001 8874.577 12695.77251.0 .001 8874.577 12695.77251.1 .001 9715.681 12962.33052.0 .001 9715.681 12962.33052.1 .001 10556.786 13196.88853.0 .001 10556.786 13196.888
31
53.1 .001 11397.891 13413.74354.0 .001 11397.891 13413.74354.1 .001 12238.995 13615.35755.0 .001 12238.995 13615.35755.1 .000 13080.100 13803.71956.0 .000 13080.100 13803.71956.1 .000 13392.236 13865.26057.0 .000 13392.236 13865.26057.1 .000 13395.991 13865.26058.0 .000 13395.991 13865.26058.1 .000 13395.991 13865.260
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 132 model evaluations and 58 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-010. Parameter Estimates
Std. Error 95% Confidence Interval Parameter
Estimate Lower Bound Upper Bound
A 13395.991 7066.690 -76394.820 103186.802Ea 13865.260 1503.059 -5232.914 32963.434
Correlations of Parameter Estimates A Ea A 1.000 .999 Ea .999 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 64.569 2 32.285Residual .000 1 .000Uncorrected Total 64.570 3 Corrected Total .041 2
Dependent variable: t7 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .988.
32
Lampiran 38. Regresi non linear untuk persamaan Arrhenius (Vitamin C) pada Guava leather dengan ketebalan 9 mm
Iteration History(b)
Residual Sum of Squares Parameter Iteration
Number(a) A Ea 1.0 143.624 .100 .1001.1 266.844 1.300 14472.2191.2 18.704 .511 -7974.1062.0 18.704 .511 -7974.1062.1 2.572 1.530 -9365.7743.0 2.572 1.530 -9365.7743.1 .833 3.573 -8124.3974.0 .833 3.573 -8124.3974.1 .152 5.615 -7883.6965.0 .152 5.615 -7883.6965.1 .193 9.698 -6152.4185.2 .106 7.087 -7477.1466.0 .106 7.087 -7477.1466.1 .108 10.031 -6377.3446.2 .099 8.374 -7043.2677.0 .099 8.374 -7043.2677.1 .096 10.949 -6209.4308.0 .096 10.949 -6209.4308.1 .088 13.524 -5651.7069.0 .088 13.524 -5651.7069.1 .089 18.674 -4635.2749.2 .083 15.950 -5209.05110.0 .083 15.950 -5209.05110.1 .081 20.801 -4383.61511.0 .081 20.801 -4383.61511.1 .073 25.653 -3829.22312.0 .073 25.653 -3829.22312.1 .075 35.356 -2819.00912.2 .069 30.008 -3412.81413.0 .069 30.008 -3412.81413.1 .067 38.719 -2622.89514.0 .067 38.719 -2622.89514.1 .060 47.430 -2082.95815.0 .060 47.430 -2082.95815.1 .062 64.852 -1099.50215.2 .056 55.116 -1684.16716.0 .056 55.116 -1684.16716.1 .054 70.489 -923.49017.0 .054 70.489 -923.49017.1 .049 85.862 -396.000
33
18.0 .049 85.862 -396.00018.1 .050 116.607 564.71618.2 .045 99.057 -17.48819.0 .045 99.057 -17.48819.1 .044 125.449 710.87420.0 .044 125.449 710.87420.1 .039 151.841 1224.03021.0 .039 151.841 1224.03021.1 .041 204.624 2158.83621.2 .036 173.912 1582.67622.0 .036 173.912 1582.67622.1 .035 218.053 2278.19823.0 .035 218.053 2278.19823.1 .031 262.194 2776.13924.0 .031 262.194 2776.13924.1 .032 350.476 3683.71924.2 .028 298.075 3114.43225.0 .028 298.075 3114.43225.1 .027 369.837 3775.74226.0 .027 369.837 3775.74226.1 .024 441.599 4257.14127.0 .024 441.599 4257.14127.1 .025 585.123 5135.36227.2 .022 498.221 4574.81328.0 .022 498.221 4574.81328.1 .021 611.466 5200.67429.0 .021 611.466 5200.67429.1 .018 724.710 5664.17330.0 .018 724.710 5664.17330.1 .019 951.199 6510.83730.2 .016 811.266 5960.83431.0 .016 811.266 5960.83431.1 .015 984.379 6549.82632.0 .015 984.379 6549.82632.1 .013 1157.492 6993.87133.0 .013 1157.492 6993.87133.1 .014 1503.718 7806.41733.2 .012 1285.374 7269.09334.0 .012 1285.374 7269.09334.1 .011 1541.136 7819.67735.0 .011 1541.136 7819.67735.1 .009 1796.898 8242.52836.0 .009 1796.898 8242.52836.1 .008 2052.661 8612.60437.0 .008 2052.661 8612.60437.1 .009 2564.186 9296.06637.2 .007 2272.121 8890.76938.0 .007 2272.121 8890.76938.1 .007 2711.042 9425.822
34
39.0 .007 2711.042 9425.82239.1 .006 3149.963 9839.82940.0 .006 3149.963 9839.82940.1 .005 3588.884 10203.00341.0 .005 3588.884 10203.00341.1 .005 4466.725 10874.41441.2 .004 3903.164 10427.11942.0 .004 3903.164 10427.11942.1 .004 4531.724 10875.50943.0 .004 4531.724 10875.50943.1 .003 5160.284 11237.20444.0 .003 5160.284 11237.20444.1 .002 5788.844 11559.06545.0 .002 5788.844 11559.06545.1 .003 7045.964 12158.08845.2 .002 6218.004 11750.68046.0 .002 6218.004 11750.68046.1 .002 7076.323 12136.41547.0 .002 7076.323 12136.41547.1 .002 7934.642 12457.04548.0 .002 7934.642 12457.04548.1 .001 8792.961 12745.77449.0 .001 8792.961 12745.77449.1 .001 9651.280 13008.27250.0 .001 9651.280 13008.27250.1 .001 11367.918 13502.17250.2 .001 10179.130 13151.31451.0 .001 10179.130 13151.31451.1 .001 11234.830 13442.62452.0 .001 11234.830 13442.62452.1 .001 12290.531 13695.94953.0 .001 12290.531 13695.94953.1 .001 13346.231 13928.78054.0 .001 13346.231 13928.78054.1 .001 14401.931 14144.15455.0 .001 14401.931 14144.15455.1 .000 15457.631 14344.48756.0 .000 15457.631 14344.48756.1 .000 16513.331 14531.72957.0 .000 16513.331 14531.72957.1 .000 16676.423 14553.50658.0 .000 16676.423 14553.50658.1 .000 16677.232 14553.50659.0 .000 16677.232 14553.50659.1 .000 16677.233 14553.507
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 134 model evaluations and 59 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-010.
35
Parameter Estimates
95% Confidence Interval Parameter
Estimate Std. Error Lower Bound Upper Bound
A 16677.233 8458.205 -90794.458 124148.924Ea 14553.507 1445.070 -3807.854 32914.867
Correlations of Parameter Estimates A Ea A 1.000 .999 Ea .999 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 63.952 2 31.976Residual .000 1 .000Uncorrected Total 63.952 3 Corrected Total .045 2
Dependent variable: t9 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .990. Lampiran 39. Regresi non linear untuk persamaan fungsi penurunan kadar air
pada Guava Leather dengan ketebalan 5 mm pada suhu pengeringan 60oC.
Iteration History(b)
Residual Sum of Squares Parameter Iteration
Number(a) K1 K2 1.0 31243.002 .000 .0001.1 10264.654 23.570 .0002.0 10264.654 23.570 .0002.1 2625.354 60.556 -.2493.0 2625.354 60.556 -.2493.1 336.181 80.429 -.2244.0 336.181 80.429 -.2244.1 329.282 80.021 -.2285.0 329.282 80.021 -.2285.1 329.242 80.097 -.2286.0 329.242 80.097 -.2286.1 329.242 80.107 -.2287.0 329.242 80.107 -.2287.1 329.242 80.109 -.2288.0 329.242 80.109 -.228
36
8.1 329.242 80.109 -.228Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 16 model evaluations and 8 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-008. Parameter Estimates
Estimate Std. Error 95% Confidence Interval Parameter Lower Bound Upper Bound k1 80.109 2.887 73.988 86.230k2 -.228 .014 -.258 -.199
Correlations of Parameter Estimates k1 k2 k1 1.000 -.698 k2 -.698 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 30913.760 2 15456.880Residual 329.242 16 20.578Uncorrected Total 31243.002 18 Corrected Total 7251.551 17
Dependent variable: ka_T5S60 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .955. Lampiran 40. Regresi non linear untuk persamaan fungsi penurunan kadar air
pada Guava Leather dengan ketebalan 5 mm pada suhu pengeringan 70oC.
Iteration History(b)
Residual Sum of Squares Parameter
Iteration Number(a) K1 K2 1.0 27290.419 .000 .0001.1 9072.977 26.726 .0002.0 9072.977 26.726 .0002.1 1886.231 66.921 -.3453.0 1886.231 66.921 -.3453.1 179.135 87.715 -.3254.0 179.135 87.715 -.3254.1 177.525 87.533 -.3285.0 177.525 87.533 -.3285.1 177.518 87.568 -.328
37
6.0 177.518 87.568 -.3286.1 177.518 87.571 -.3297.0 177.518 87.571 -.3297.1 177.518 87.572 -.329
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 14 model evaluations and 7 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-008. Parameter Estimates
Estimate Std. Error 95% Confidence Interval Parameter Lower Bound Upper Bound k1 87.572 2.762 81.554 93.589k2 -.329 .017 -.367 -.290
Correlations of Parameter Estimates k1 k2 k1 1.000 -.672 k2 -.672 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 27112.901 2 13556.450Residual 177.518 12 14.793Uncorrected Total 27290.419 14 Corrected Total 7384.818 13
Dependent variable: ka_T5S70 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .976. Lampiran 41. Regresi non linear untuk persamaan fungsi penurunan kadar air
pada Guava Leather dengan ketebalan 5 mm pada suhu pengeringan 80oC.
Iteration History(b)
Residual Sum of Squares Parameter
Iteration Number(a) K1 K2 1.0 19969.277 .000 .0001.1 6160.735 30.151 .0002.0 6160.735 30.151 .0002.1 744.984 69.244 -.4423.0 744.984 69.244 -.4423.1 87.165 84.629 -.4424.0 87.165 84.629 -.442
38
4.1 87.165 84.628 -.4425.0 87.165 84.628 -.4425.1 87.165 84.628 -.442
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 10 model evaluations and 5 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-008. Parameter Estimates
Estimate Std. Error 95% Confidence Interval Parameter Lower Bound Upper Bound k1 84.628 2.448 79.090 90.167k2 -.442 .022 -.492 -.393
Correlations of Parameter Estimates k1 k2 k1 1.000 -.647 k2 -.647 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 19882.112 2 9941.056Residual 87.165 9 9.685Uncorrected Total 19969.277 11 Corrected Total 5798.110 10
Dependent variable: ka_T5S80 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .985. Lampiran 42. Regresi non linear untuk persamaan fungsi penurunan kadar air
pada Guava Leather dengan ketebalan 7 mm pada suhu pengeringan 60oC.
Iteration History(b)
Residual Sum of Squares Parameter
Iteration Number(a) K1 K2 1.0 43509.479 .000 .0001.1 18399.317 18.298 .0002.0 18399.317 18.298 .0002.1 6007.869 49.928 -.1493.0 6007.869 49.928 -.1493.1 349.412 80.980 -.1694.0 349.412 80.980 -.1694.1 327.024 81.511 -.164
39
5.0 327.024 81.511 -.1645.1 326.968 81.406 -.1646.0 326.968 81.406 -.1646.1 326.968 81.396 -.1647.0 326.968 81.396 -.1647.1 326.968 81.395 -.1648.0 326.968 81.395 -.1648.1 326.968 81.395 -.164
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 16 model evaluations and 8 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-008. Parameter Estimates
Estimate Std. Error 95% Confidence Interval Parameter Lower Bound Upper Bound k1 81.395 2.100 77.050 85.740k2 -.164 .007 -.178 -.149
Correlations of Parameter Estimates k1 k2 k1 1.000 -.711 k2 -.711 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 43182.511 2 21591.256Residual 326.968 23 14.216Uncorrected Total 43509.479 25 Corrected Total 10029.263 24
Dependent variable: ka_T7S60 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .967. Lampiran 43. Regresi non linear untuk persamaan fungsi penurunan kadar air
pada Guava Leather dengan ketebalan 7 mm pada suhu pengeringan 70oC.
Iteration History(b)
Residual Sum of Squares Parameter
Iteration Number(a) K1 K2 1.0 38937.877 .000 .0001.1 14327.647 21.822 .0002.0 14327.647 21.822 .000
40
2.1 4120.314 57.470 -.1993.0 4120.314 57.470 -.1993.1 220.277 83.427 -.1934.0 220.277 83.427 -.1934.1 219.178 83.326 -.1945.0 219.178 83.326 -.1945.1 219.174 83.351 -.1946.0 219.174 83.351 -.1946.1 219.174 83.353 -.1947.0 219.174 83.353 -.1947.1 219.174 83.353 -.194
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 14 model evaluations and 7 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-008. Parameter Estimates
Estimate Std. Error 95% Confidence Interval Parameter Lower Bound Upper Bound k1 83.353 2.030 79.104 87.602k2 -.194 .008 -.211 -.177
Correlations of Parameter Estimates k1 k2 k1 1.000 -.705 k2 -.705 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 38718.703 2 19359.352Residual 219.174 19 11.535Uncorrected Total 38937.877 21 Corrected Total 8991.176 20
Dependent variable: ka_T7S70 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .976.
41
Lampiran 44. Regresi non linear untuk persamaan fungsi penurunan kadar air pada Guava Leather dengan ketebalan 7 mm pada suhu pengeringan 80oC.
Iteration History(b)
Residual Sum of Squares Parameter
Iteration Number(a) K1 K2 1.0 30939.778 .000 .0001.1 10454.020 24.254 .0002.0 10454.020 24.254 .0002.1 2505.172 61.874 -.2693.0 2505.172 61.874 -.2693.1 91.750 83.450 -.2454.0 91.750 83.450 -.2454.1 84.725 83.272 -.2505.0 84.725 83.272 -.2505.1 84.705 83.325 -.2516.0 84.705 83.325 -.2516.1 84.705 83.329 -.2517.0 84.705 83.329 -.2517.1 84.705 83.330 -.251
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 14 model evaluations and 7 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-008. Parameter Estimates
Estimate Std. Error 95% Confidence Interval Parameter Lower Bound Upper Bound k1 83.330 1.561 80.003 86.656k2 -.251 .008 -.268 -.234
Correlations of Parameter Estimates k1 k2 k1 1.000 -.692 k2 -.692 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 30855.074 2 15427.537Residual 84.705 15 5.647Uncorrected Total 30939.778 17 Corrected Total 7705.242 16
42
Dependent variable: ka_T7S80 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .989. Lampiran 45. Regresi non linear untuk persamaan fungsi penurunan kadar air
pada Guava Leather dengan ketebalan 9 mm pada suhu pengeringan 60oC.
Iteration History(b)
Residual Sum of Squares Parameter
Iteration Number(a) K1 K2 1.0 66219.066 .000 .0001.1 29138.050 17.961 .0002.0 29138.050 17.961 .0002.1 8684.419 51.416 -.0973.0 8684.419 51.416 -.0973.1 126.836 81.536 -.1034.0 126.836 81.536 -.1034.1 119.017 81.592 -.1015.0 119.017 81.592 -.1015.1 119.016 81.578 -.1016.0 119.016 81.578 -.1016.1 119.016 81.578 -.101
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 12 model evaluations and 6 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-008. Parameter Estimates
Estimate Std. Error 95% Confidence Interval Parameter Lower Bound Upper Bound k1 81.578 .959 79.617 83.539k2 -.101 .002 -.106 -.097
Correlations of Parameter Estimates k1 k2 k1 1.000 -.742 k2 -.742 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 66100.050 2 33050.025Residual 119.016 29 4.104Uncorrected Total 66219.066 31 Corrected Total 10803.515 30
43
Dependent variable: ka_T9S60 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .989. Lampiran 46. Regresi non linear untuk persamaan fungsi penurunan kadar air
pada Guava Leather dengan ketebalan 9 mm pada suhu pengeringan 70oC.
Iteration History(b)
Residual Sum of Squares Parameter
Iteration Number(a) K1 K2 1.0 53152.796 .000 .0001.1 21426.655 19.791 .0002.0 21426.655 19.791 .0002.1 6629.698 54.109 -.1363.0 6629.698 54.109 -.1363.1 169.946 83.437 -.1384.0 169.946 83.437 -.1384.1 169.627 83.468 -.1375.0 169.627 83.468 -.1375.1 169.627 83.460 -.1376.0 169.627 83.460 -.1376.1 169.627 83.459 -.1377.0 169.627 83.459 -.1377.1 169.627 83.459 -.137
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 14 model evaluations and 7 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-008. Parameter Estimates
Estimate Std. Error 95% Confidence Interval Parameter Lower Bound Upper Bound k1 83.459 1.367 80.643 86.275k2 -.137 .004 -.145 -.129
Correlations of Parameter Estimates k1 k2 k1 1.000 -.723 k2 -.723 1.000
44
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 52983.169 2 26491.585Residual 169.627 25 6.785Uncorrected Total 53152.796 27 Corrected Total 10851.275 26
Dependent variable: ka_T9S70 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .984. Lampiran 47. Regresi non linear untuk persamaan fungsi penurunan kadar air
pada Guava Leather dengan ketebalan 9 mm pada suhu pengeringan 80oC.
Iteration History(b)
Residual Sum of Squares Parameter
Iteration Number(a) K1 K2 1.0 42038.342 .000 .0001.1 17207.939 18.970 .0002.0 17207.939 18.970 .0002.1 5357.338 51.816 -.1613.0 5357.338 51.816 -.1613.1 182.486 80.851 -.1684.0 182.486 80.851 -.1684.1 179.869 80.970 -.1665.0 179.869 80.970 -.1665.1 179.864 80.941 -.1666.0 179.864 80.941 -.1666.1 179.864 80.939 -.1667.0 179.864 80.939 -.1667.1 179.864 80.939 -.166
Derivatives are calculated numerically. a Major iteration number is displayed to the left of the decimal, and minor iteration number is to the right of the decimal. b Run stopped after 14 model evaluations and 7 derivative evaluations because the relative reduction between successive residual sums of squares is at most SSCON = 1.00E-008. Parameter Estimates
Estimate Std. Error 95% Confidence Interval Parameter Lower Bound Upper Bound k1 80.939 1.657 77.493 84.384k2 -.166 .006 -.178 -.154
45
Correlations of Parameter Estimates k1 k2 k1 1.000 -.715 k2 -.715 1.000
ANOVA(a)
Source Sum of
Squares df Mean
Squares Regression 41858.477 2 20929.239Residual 179.864 21 8.565Uncorrected Total 42038.342 23 Corrected Total 8931.139 22
Dependent variable: ka_T9S80 a R squared = 1 - (Residual Sum of Squares) / (Corrected Sum of Squares) = .980.