PENGARUH CARA PENGERINGAN DAN PENAMBAHAN KACANG HIJAU TERHADAP SIFAT WARNA DAN TINGKAT KESUKAAN BERAS ANALOG OYEK

  PENGARUH CARA PENGERINGAN DAN PENAMBAHAN KACANG HIJAU TERHADAP SIFAT WARNA DAN TINGKAT KESUKAAN BERAS ANALOG OYEK SKRIPSI Oleh

INDAH PUSPITA DEWI 13031014 PROGRAM STUDI TEKNOLOGI HASIL PERTANIAN FAKULTAS AGROINDUSTRI UNIVERSITAS MERCU BUANA YOGYAKARTA

  LAMPIRAN 1. ANALISIS KIMIA BAHAN DASAR a.

  Analisis Kadar Air

• Ditimbang bahan yang telah dihaluskan sebanyak 1 – 2 gram dalam botol timbang yang telah bersih dan kering dan diketahui berat konstannya.
• – 5 jam, kemudian didinginkan dalam desikator dan ditimbang.
• Dikeringkan dalam oven padasuhu 100 – 105
• Dipanaskan kembali dalam oven selama 30 menit didinginkan dalam desikator dan ditimbang lagi.
• Perlakuan tersebut diulangi sampai tercapai berat konstan
• Pengurangan berat merupakan banyaknya air dalam bahan.

  C selama 3

  (%) = ( + ) −

  − 100% b.

  Analisis Protein (metode Kjedahl) (AOAC,1984).

• Menimbang 2-5 g sampel ke dalam labu kjedahl.c
• Menambahkan 10 g Kalium sulfat (K

  2 SO

  4

  ), 0,7 g merkuri oksida (HgO) atau 0,5g tembaga sulfat (CuSO 4.

  5H

  2 O) dan 20 ml asam sulfat

  pekat (H

2 SO 4 ).

• Destruksi sampel dalam ruang asam dengan panas yang rendah sampai tidak berasap lagi.
• Destruksi diteruskan dengan panas yang lebih tinggi hingga cairan menjadi jernih. Kemudiana didinginkan
• secara kuantitatif ke dalam alat destilasi

  Melarutkan destruat dengan 50 ml aquadest dan kemudian pindahkan

• yang berisi 50 ml asam borat 3 % dan beberapa tetes indikator (campuran metil biru dan metil merah (1:2) dalam etanol 95%).

  Menghubungkan alat destilasi dengan penampung erlenmeyer 500 ml

• (perubahan warna jernih menjadi coklat)

  Mendidihkan sekitar 15 menit, menambahkan natrium hidroksida 60 %

  Melakukan destilasi sampai volume penampung mencapai 200 ml

• Titrasi destilat dengan asam klorida (HCl) 0,1 N.
• Mengerjakan blanko menggunakan aquadest sebagai pengganti
• sampel. Perhitungan :

  V1−V2

  Kadar Nitrogen (g/100g) = × 0,0014 × N

  Keterangan : V1 = jumlah ml HCl yang digunakan pada sampel V2 = jumlah ml HCl yang digunakan pada blanko B = berat sampel c. Analisis lemak (Metode Soxhlet)

• sebanyak 2 g , lalu dibungkus dengan kertas saring yang telah diketahui beratnya. Sampel dimasukkan dalam labu soxhlet ditambah

  Sampel dari hasil kadar air dihaluskan lalu ditimbang masing-masing dengan pelarut (Petroleum Eter) sampai 1/3 bagian labu lalu diekstraksi selama 3-4 jam.

  Angkat sampel yang terlarut dalam labu dan masukkan dalam oven,

• didinginkan dalam desikator, kemudian ditimbang sampai berat konstan (Soedarmaji, 1997). Perhitungan : berat lemak (g)

  %lemak = berat awal (g) X 100% d.

  Analisis serat kasar (Metode Gravimetri) Sampel-sampel yang telah diekstrak lemaknya, dimasukkan ke dalam

• erlenmeyer ditambah dengan anti buih serta batu didih.
• SO 0,25 N sebanyak 200 ml dan didihkan

  2

  

4

Kemudian ditambahkan H

  selama 30 menit. Residu yang terbentuk disaring dan dicuci dengan aquadest panas.

• meyer dengan menambahkan NaOH 0,25 N sebanyak 200 ml kemudian dididihkan kembali selam 30 menit.

  Residu yang terbentuk pada kertas saring dimasukkan dalam erlen

• beratnya.

  Setelah itu residu disaring dengan kertas saring yang telah diketahui

  SO 10% dan alkohol 95 %

  2

• Kertas saring yang berisi residu dikeringkan dalam oven lalu di abukan

  4 Residu kemudian dicuci dengan K

• , dan ditimbang sampai berat konstan (Soedarmaji, 1997) Perhitungan :
• %protein+%amilosa+%amilopektin) (Nielsen, 1998)

  %serat kasar = berat serat kasar berat sampel x 100% e.

  Oven 2.45 .759

  40 Kabinet 2.90 1.081

  40 Matahari 2.83 .984

  60 Total Oven 2.67 .944

  20 Total 2.63 .920

  20 Kabinet 2.80 1.056

  20 Matahari 2.65 .933

  60 Rastelo + Kacang Hijau

  Analisis karbohidrat (by different)

  20 Total 2.97 1.057

  20 Kabinet 3.00 1.124

  20 Matahari 3.00 1.026

  Deviation N Rastelo Oven 2.90 1.071

  Dependent Variable: Bau Jenis_Sampel Pengeringan Mean Std.

  LAMPIRAN 2. HASIL UJI STATISTIK 1. Hasil uji statistik organoleptik beras analog dengan cara pengeringan Descriptive Statistics

  Carbohidrate by difference = 100% - (%air + %abu +%lemak

  40 Total 2.80 1.001 120

  

Tests of Between-Subjects Effects

  Dependent Variable: Bau Type III Sum Mean Source of Squares df Square F Sig.

  a

  Corrected Model 4.700 5 .940 .936 .461 Intercept 940.800 1 940.800 936.692 .000 Jenis_Sampel 3.333 1 3.333 3.319 .071 Pengeringan 1.050 2 .525 .523 .594 Jenis_Sampel *

  .317 2 .158 .158 .854 Pengeringan Error 114.500 114 1.004 Total 1060.000 120 Corrected Total 119.200 119

  

ANOVA

  Bau Sum of Mean Squares df Square F Sig.

  Between 4.700 5 .940 .936 .461

  Groups Within Groups 114.500 114 1.004 Total 119.200 119

  Bau a

  Duncan Subset for alpha = 0.05

  Interaksi N

  1 Rastelo++,Oven

  20

  2.45 Rastelo++,Matah

  20

  2.65 ari Rastelo++,Kabine

  20

  2.80 t Rastelo,Oven

  20

  2.90 Rastelo,Matahari

  20

  3.00 Rastelo,Kabinet

  20

  3.00 Sig. .133

  

Tests of Between-Subjects Effects

  Dependent Variable: Warna Type III Sum Mean Source of Squares df Square F Sig.

  a

  Corrected Model 15.767 5 3.153 2.426 .040 Intercept 952.033 1 952.033 732.333 .000 Jenis_Sampel 12.033 1 12.033 9.256 .003 Pengeringan .117 2 .058 .045 .956 Jenis_Sampel *

  3.617 2 1.808 1.391 .253 Pengeringan Error 148.200 114 1.300 Total 1116.000 120 Corrected Total 163.967 119 a.

  R Squared = .096 (Adjusted R Squared = .057) Warna Duncana,b

  Subset Pengeringan N

  1 Oven

  40

  2.78 Matahari

  40

  2.82 Kabinet

  40

  2.85 Sig. .784

  

Tests of Between-Subjects Effects

  Dependent Variable: Tekstur Type III Sum Mean Source of Squares df Square F Sig.

  a

  Corrected Model 15.967 5 3.193 2.493 .035 Intercept 1216.033 1 1216.033 949.505 .000 Jenis_Sampel 12.033 1 12.033 9.396 .003 Pengeringan 3.617 2 1.808 1.412 .248 Jenis_Sampel *

  .317 2 .158 .124 .884 Pengeringan Error 146.000 114 1.281 Total 1378.000 120 Corrected Total 161.967 119 Tekstur Duncana,b

  Subset Pengeringan N

  1 Oven

  40

  2.97 Matahari

  40

  3.18 Kabinet

  40

  3.40 Sig. .115

  

ANOVA

  Tekstur Sum of Mean Squares df Square F Sig.

  Between 15.967 5 3.193 2.493 .035

  Groups Within Groups 146.000 114 1.281 Total 161.967 119

  Tekstur a

  Duncan Subset for alpha = 0.05

  Interaksi N

  1

  2

  3 Rastelo++,Oven

  20

  2.60 Rastelo++,Matah

  20

  2.85

  2.85 ari Rastelo++,Kabine

  20

  3.15

  3.15

  3.15 t Rastelo,Oven

  20

  3.35

  3.35

  3.35 Rastelo,Matahari

  20

  3.50

  3.50 Rastelo,Kabinet

  20

  3.65 Sig. .057 .100 .208 Means for groups in homogeneous subsets are displayed.

  a.

  Uses Harmonic Mean Sample Size = 20.000.

  

Tests of Between-Subjects Effects

  Dependent Variable: Keseluruhan Type III Sum Mean Source of Squares df Square F Sig.

  a

  Corrected Model 5.942 5 1.188 1.157 .335 Intercept 1074.008 1 1074.008 1046.023 .000 Jenis_Sampel 3.008 1 3.008 2.930 .090 Pengeringan 2.067 2 1.033 1.006 .369 Jenis_Sampel *

  .867 2 .433 .422 .657 Pengeringan Error 117.050 114 1.027 Total 1197.000 120 Corrected Total 122.992 119 a.

  R Squared = .048 (Adjusted R Squared = .007) Keseluruhan Duncana,b

  Subset Pengeringan N

  1 Oven

  40

  2.88 Matahari

  40

  2.92 Kabinet

  40

  3.18 Sig. .216

  ANOVA

  Keseluruhan Sum of Mean Squares df Square F Sig.

  Between 5.942 5 1.188 1.157 .335

  Groups Within Groups 117.050 114 1.027 Total 122.992 119

  Keseluruhan a

  Duncan Subset for alpha = 0.05

  Interaksi N

  1 Rastelo++,Oven

  20

  2.60 Rastelo++,Matah

  20

  2.80 ari Rastelo,Matahari

  20

  3.05 Rastelo++,Kabine

  20

  3.10 t Rastelo,Oven

  20

  3.15 Rastelo,Kabinet

  20

  3.25 Sig. .078 2.

   Hasil uji statistik organoleptik nasi dari beras analog dengan cara pengeringan

Tests of Between-Subjects Effects

  Dependent Variable: Bau Type III Sum Mean Source of Squares df Square F Sig.

  a

  Corrected Model 142.342 5 28.468 17.807 .000 Intercept 1864.408 1 1864.408 1166.214 .000 Jenis_sampel 88.408 1 88.408 55.301 .000 Pengeringan 42.467 2 21.233 13.282 .000 Jenis_sampel *

  11.467 2 5.733 3.586 .031 Pengeringan Error 182.250 114 1.599 Total 2189.000 120 Corrected Total 324.592 119

  a. R Squared = .439 (Adjusted R Squared = .414)

  Grand Mean Dependent Variable: Bau

  95% Confidence Interval Lower Upper

  Mean Std. Error Bound Bound 3.942 .115 3.713 4.170

  

Tests of Between-Subjects Effects

  Dependent Variable: Warna Type III Sum Mean Source of Squares df Square F Sig.

  a

  Corrected Model 5.542 5 1.108 .686 .635 Intercept 1353.408 1 1353.408 838.297 .000 Jenis_sampel 3.008 1 3.008 1.863 .175 Pengeringan 1.267 2 .633 .392 .676 Jenis_sampel *

  1.267 2 .633 .392 .676 Pengeringan Error 184.050 114 1.614 Total 1543.000 120 Corrected Total 189.592 119

  a. R Squared = .029 (Adjusted R Squared = -.013) Warna Duncana,b

  Subset Pengeringan N

  1 Oven

  40

  3.23 Kabinet

  40

  3.37 Matahari

  40

  3.47 Sig. .412

  ANOVA

  Warna Sum of Mean Squares df Square F Sig.

  Between 5.542 5 1.108 .686 .635

  Groups Within Groups 184.050 114 1.614 Total 189.592 119

  Warna a

  Duncan Subset for alpha = 0.05

  Interaksi N

  1 Rastelo,Oven

  20

  3.05 Rastelo,Matahari

  20

  3.20 Rastelo,Kabinet

  20

  3.35 Rastelo++,Oven

  20

  3.40 Rastelo++,Kabine

  20

  3.40 t Rastelo++,Matah

  20

  3.75 ari Sig. .132

  

Tests of Between-Subjects Effects

  Dependent Variable: Tekstur Type III Sum Mean Source of Squares df Square F Sig.

  a

  Corrected Model 37.175 5 7.435 5.339 .000 Intercept 1665.075 1 1665.075 1195.707 .000 Jenis_sampel 12.675 1 12.675 9.102 .003 Pengeringan 13.650 2 6.825 4.901 .009 Jenis_sampel *

  10.850 2 5.425 3.896 .023 Pengeringan Error 158.750 114 1.393 Total 1861.000 120 Corrected Total 195.925 119

  Tekstur a,b

  Duncan Subset

  Pengeringan N

  1

  2 Oven

  40

  3.25 Matahari

  40

  3.92 Kabinet

  40

  4.00 Sig. 1.000 .777

  

Tests of Between-Subjects Effects

  Dependent Variable: Rasa Type III Sum Mean Source of Squares df Square F Sig.

  a

  Corrected Model 24.167 5 4.833 2.672 .025 Intercept 1657.633 1 1657.633 916.441 .000 Jenis_sampel 13.333 1 13.333 7.371 .008 Pengeringan 6.317 2 3.158 1.746 .179 Jenis_sampel *

  4.517 2 2.258 1.249 .291 Pengeringan Error 206.200 114 1.809 Total 1888.000 120 Corrected Total 230.367 119

  a. R Squared = .105 (Adjusted R Squared = .066) Rasa Duncana,b

  Subset Pengeringan N

  1 Matahari

  40

  3.48 Oven

  40

  3.65 Kabinet

  40

  4.03 Sig. .086

  

Tests of Between-Subjects Effects

  Dependent Variable: Keseluruhan Type III Sum Mean Source of Squares df Square F Sig.

  a

  Corrected Model 34.700 5 6.940 4.737 .001 Intercept 1872.300 1 1872.300 1278.097 .000 Jenis_sampel 22.533 1 22.533 15.382 .000 Pengeringan 10.850 2 5.425 3.703 .028 Jenis_sampel *

  1.317 2 .658 .449 .639 Pengeringan Error 167.000 114 1.465 Total 2074.000 120 Corrected Total 201.700 119

  a. R Squared = .172 (Adjusted R Squared = .136) Keseluruhan Duncana,b

  Subset Pengeringan N

  1

  2 Oven

  40

  3.73 Matahari

  40

  3.75 Kabinet

  40

  4.38 Sig. .927 1.000

  ANOVA

  Keseluruhan Sum of Mean Squares df Square F Sig.

  Between 34.700 5 6.940 4.737 .001

  Groups Within Groups 167.000 114 1.465 Total 201.700 119

  Keseluruhan a

  Duncan Subset for alpha =

  0.05 Interaksi N

  1

  2 Rastelo++,Matah

  20

  3.35 ari Rastelo++,Oven

  20

  3.40 Rastelo++,Kabine

  20

  3.80 t Rastelo,Oven

  20

  4.05 Rastelo,Matahari

  20

  4.15 Rastelo,Kabinet

  20

  4.95 Sig. .064 1.000 Means for groups in homogeneous subsets are displayed.

  a. Uses Harmonic Mean Sample Size = 20.000.

3. Hasil uji statistik kadar air beras analog dengan cara pengeringan

  

Tests of Between-Subjects Effects

  Dependent Variable: Kadar_Air Type III Sum Mean Source of Squares df Square F Sig.

  a

  Corrected Model 10.136 5 2.027 23.826 .000 Intercept 2247.708 1 2247.708 26417.725 .000 Pengeringan 8.777 2 4.389 51.580 .000 Jenis_Sampel .025 1 .025 .288 .595 Pengeringan *

  1.334 2 .667 7.840 .002 Jenis_Sampel Error 2.552 30 .085 Total 2260.396

  36 Corrected Total 12.688

  35 a. R Squared = .799 (Adjusted R Squared = .765) Kadar_Air Duncana,b

  Subset Pengeringan N

  1

  2

  3 Matahari 12 7.2192 Kabinet 12 8.1150

  o

  50 C

  o

  Oven 40 C 12 8.3708 Sig. 1.000 1.000 1.000

  Oneway

ANOVA

  Kadar_Air Sum of Mean Squares df Square F Sig.

  Between 10.136 5 2.027 23.826 .000

  Groups Within Groups 2.552 30 .085 Total 12.688

  35 Kadar_Air

  a

  Duncan Subset for alpha = 0.05

  Interaksi N

  1

  2

  3

  4 Rastelo Matahari 6 7.1017 Rastelo+ Matahari 6 7.3367 Rastelo+ Kabinet 6 7.8733

  o

  50 C

  o

  Rastelo Oven 40 C 6 8.1683 8.1683

  o

  Rastelo Kabinet 50 C 6 8.3567 8.3567

  o

  Rastelo+ Oven 40 C 6 8.5733 Sig. .173 .090 .272 .208

4. Hasil uji statistik warna beras analog dengan cara pengeringan a

  

Multivariate Tests

  Hypothes Effect Value F is df Error df Sig.

  b

  Intercept Pillai's Trace .955 310.025 2.000 29.000 .000 Wilks'

  b

  .045 310.025 2.000 29.000 .000 Lambda Hotelling's

  b

  21.381 310.025 2.000 29.000 .000 Trace Roy's Largest

  b

  21.381 310.025 2.000 29.000 .000 Root

  Pengeringan Pillai's Trace .199 1.653 4.000 60.000 .173 Wilks'

  b

  .805 1.663 4.000 58.000 .171 Lambda Hotelling's

  .238 1.669 4.000 56.000 .170 Trace Roy's Largest

  c

  .220 3.295 2.000 30.000 .051 Root

  b

  Jenis_Sampel Pillai's Trace .853 83.980 2.000 29.000 .000 Wilks'

  b

  .147 83.980 2.000 29.000 .000 Lambda Hotelling's

  b

  5.792 83.980 2.000 29.000 .000 Trace Roy's Largest

  b

  5.792 83.980 2.000 29.000 .000 Root

  Pengeringan * Pillai's Trace .389 3.625 4.000 60.000 .010 Jenis_Sampel

  Wilks'

  b

  .612 4.040 4.000 58.000 .006 Lambda Hotelling's

  .633 4.434 4.000 56.000 .003 Trace Roy's Largest

  c

  .631 9.465 2.000 30.000 .001 Root

  a. Design: Intercept + Pengeringan + Jenis_Sampel + Pengeringan * Jenis_Sampel

  b. Exact statistic b.

  

Tests of Between-Subjects Effects

  35 Yellow 4.056

  o

  C 12 .2833 .2833 Oven 40

  o

  50

  2 Matahari 12 .2417 Kabinet

  1

  Pengeringan N Subset

  a,b

  Duncan

  Red

  b. R Squared = .781 (Adjusted R Squared = .745)

  a. R Squared = .793 (Adjusted R Squared = .758)

  35

  36 Corrected Total Red 1.343

  Source Dependent Variable

  36 Yellow 15.730

  Total Red 4.290

  Error Red .278 30 .009 Yellow .888 30 .030

  Red .112 2 .056 6.018 .006 Yellow .267 2 .134 4.512 .019

  Yellow 2.834 1 2.834 95.694 .000 Pengeringan * Jenis_Sampel

  Yellow .067 2 .034 1.135 .335 Jenis_Sampel Red .902 1 .902 97.275 .000

  Yellow 11.674 1 11.674 394.231 .000 Pengeringan Red .051 2 .025 2.725 .082

  5 .634 21.398 .000 Intercept Red 2.947 1 2.947 317.635 .000

  b

  5 .213 22.952 .000 Yellow 3.168

  a

  Corrected Model Red 1.065

  Squares df Mean Square F Sig.

  Type III Sum of

  C 12 .3333 Sig. .298 .213

  Yellow a,b

  Duncan Subset

  Pengeringan N

  1 Matahari 12 .5083

  o

  Oven 40 C 12 .6000 Kabinet 12 .6000

  o

  50 C Sig. .228

  Oneway

ANOVA

  Sum of Mean Squares df Square F Sig. Red Between

  1.065 5 .213 22.952 .000 Groups Within Groups .278 30 .009 Total 1.343

  35 Yello Between 3.168 5 .634 21.398 .000 w Groups

  Within Groups .888 30 .030 Total 4.056

  35 Red

  a

  Duncan Subset for alpha = 0.05

  Interaksi N

  1

  2

  3

  o

  Ratelo Oven 40 C 6 .1000 Rastelo Matahari 6 .1000

  o

  Ratelo Kabinet 50 C 6 .1833 Rastelo+ Matahari 6 .3833 Rastelo+ Kabinet 6 .3833

  o

  50 C

  o

  Rastelo+ Oven 40 C 6 .5667 Means for groups in homogeneous subsets are displayed.

  Yellow

  o

  C 6 1.0000 Sig. .065 .618 .053 Means for groups in homogeneous subsets are displayed.

  o

  C 6 .8000 .8000 Rastelo+ Oven 40

  o

  50

  C 6 .4000 Rastelo+ Matahari 6 .7500 Rastelo+ Kabinet

  C 6 .2000 Rastelo Matahari 6 .2667 Ratelo Kabinet 50

  Duncan

  o

  3 Ratelo Oven 40

  2

  1

  Interaksi N Subset for alpha = 0.05

  a

  a. Uses Harmonic Mean Sample Size = 6.000.

4. Hasil uji statistik warna nasi dari beras analog dengan cara pengeringan

  Effect Value F Hypothesis df Error df Sig.

  b

  2.000 29.000 .000

  b

  2.000 29.000 .000 Wilks' Lambda .113 113.800

  b

  2.000 30.000 .054 Jenis_Sampel Pillai's Trace .887 113.800

  c

  .215 3.228

  .232 1.622 4.000 56.000 .182 Roy's Largest Root

  4.000 58.000 .183 Hotelling's Trace

  Wilks' Lambda .810 1.615

  Intercept Pillai's Trace .984 887.447

  2.000 29.000 .000 Pengeringan Pillai's Trace .193 1.605 4.000 60.000 .185

  b

  61.203 887.447

  2.000 29.000 .000 Roy's Largest Root

  b

  61.203 887.447

  2.000 29.000 .000 Hotelling's Trace

  b

  

Multivariate Tests

a

  b Hotelling's

  2.000 29.000 .000 Wilks' Lambda .016 887.447

  b

  7.848 113.800 2.000 29.000 .000 Trace Roy's Largest

  b

  7.848 113.800 2.000 29.000 .000 Root

  Pengeringan * Pillai's Trace .185 1.531 4.000 60.000 .205

  b

  Jenis_Sampel Wilks' Lambda .821 1.503 4.000 58.000 .213 Hotelling's

  .210 1.473 4.000 56.000 .223 Trace Roy's Largest

  c

  .165 2.470 2.000 30.000 .102 Root c.

  R Squared = .757 (Adjusted R Squared = .717)

  Red a,b

  Duncan Subset

  Pengeringan N

  1

  o

  Oven 40 C 12 .6833 Matahari 12 .6917 Kabinet 12 .7250

  o

  50 C Sig. .347

  Yellow a,b

  Duncan Subset

  Pengeringan N

  1 Kabinet 12 1.5417

  o

  50 C

  o

  Oven 40 C 12 1.6750 Matahari 12 1.9167 Sig. .065

  Oneway

ANOVA

  Sum of Squares df Mean Square F Sig. Red Between

  2.177 5 .435 43.055 .000 Groups Within Groups .303 30 .010 Total 2.480

  35 Y Between Groups 19.459 5 3.892 18.720 .000 el Within Groups 6.237 30 .208 lo Total

  25.696

  35 w

  Red a

  Duncan Subset for alpha =

  0.05 Interaksi N

  1

  2 Rastelo Matahari 6 .4333

  o

  Rastelo Oven 40 C 6 .4667

  o

  Rastelo Kabinet 50 C 6 .4667

  o

  Rastelo+ Oven 40 C 6 .9000 Rastelo+ Matahari 6 .9500 Rastelo+ Kabinet 6 .9833

  o

  50 C Sig. .594 .185

  Yellow a

  Duncan Subset for alpha = 0.05

  Interaksi N

  1

  2

  3 Rastelo Matahari 6 1.0000 Rastelo Oven 40oC 6 1.0167 Rastelo Kabinet 6 1.0167 50oC

• – berat botol kosong Sampel Akhir = berat botol oven konstan - berat botol kosong Kadar air (%) =

  1,0110 −0,3987 1,0110

  × 100% = 67,69% B1.U3 Kadar air (%) =

  1,1806 −0,5652 1,1806

  × 100% = 52,13% B2.U1 Kadar air (%) =

  1,0368 −0,4107 1,0368

  × 100% = 60,39% 60,75%

  B2.U2 Kadar air (%) =

  × 100% = 60,56% B3.U3

  B1.U2 Kadar air (%) =

  Kadar air (%) =

  1,0404 −0,4028 1,0404

  × 100% = 61,28% Rata-rata Kadar Air (%

  

w

  /

  

b

  1,000 −0,3291 1,0000

  × 100% = 57,83% 59,02%

  Rastelo+ Oven 40oC 6 2.3333 2.3333 Rastelo+ Matahari 6 2.8333 Sig. .953 .319 .067

  B1 U1 10,5173 11,5173 1,0000 10,9390 0,4217 U2

  Lampiran 3. Hasil Uji Proksimat Bahan Dasar atau Ubi Kayu Jenis Putih 1. Kadar Air

  Batch Ulangan Botol kosong

  (g) Botol+

  Sampel (g)

  Sampel (g)

  Botol oven konstan (g) Sampel akhir (g)

  16,0212 17,0212 1,0000 16,3503 0,3291 U3 10,3779 11,5585 1,1806 10,9431 0,5652

  1,000 −0,4217 1,0000

  B2 U1 12,7325 13,7693 1,0368 13,1432 0,4107

  U2 11,2328 12,2438 1,0110 11,6315 0,3987 U3

  12,6151 13,6555 1,0404 13,0179 0,4028 Perhitungan : Sampel = (berat boto l+ sampel)

  berat sampel − berat sampel akhir berat sampel

  × 100% Kode sampel Perhitungan Rata-rata

  B1.U1 Kadar air (%) =

  ) 59,88 %

2. Kadar Abu Batch.

  Ulangan Cawan kosong (g)

  Cawan+ Sampel (g)

  Sampel (g)

  Cawan oven konstan (g) Sampel akhir (g)

  B1.U1 20,3772 25,3788 5,0016 20,4174 0,0402

  B1.U2 17,7864 22,7865 5,0001 17,8230 0,0366 B1.U3

  20,9758 25,9765 5,0007 21,0128 0,0370 B2.U1

  20,3772 25,3788 5,0016 20,4174 0,0402 B2.U2

  17,7864 22,7865 5,0001 17,8230 0,0366 B2.U3 20,9758 25,9765 5,0007 21,0128 0,0370

  Perhitungan : Sampel = (berat cawan + sampel)

• – berat cawan kosong Sampel akhir = berat cawan oven konstan
• – berat cawan kosng Kadar Abu (%) =

  × 100% Kode sampel Perhitungan Rata-rata

  5,0016 −0,0402 5,0016

  × 100% = 0,74% Rata-rata Kadar Abu (%) 0,76 %

  5,0007 −0,0370 5,0007

  Kadar abu (%) =

  × 100% = 0,73% B3.U3

  5,0001 −0,0366 5,0001

  B2.U2 Kadar abu (%) =

  × 100% = 0,80% 0,76%

  × 100% = 0,74% B2.U1 Kadar abu (%) =

  B1.U1 Kadar abu (%) =

  5,0007 −0,0370 5,0007

  Kadar abu (%) =

  × 100% = 0,73% B1.U3

  5,0001 −0,036 5,0001

  B1.U2 Kadar abu (%) =

  berat sampel − berat sampel akhir berat sampel

  5,0016 −0,0402 5,0016

  × 100% = 0,80% 0,76%

3. Kadar Protein

  Batch. Berat faktor TIitrasi N N HCl

  Ulangan sampel konversi 0,0584 0,56 14,008 6,25 0,02

  B1.U1 0,0544 0,58 14,008 6,25 0,02

  B1.U2 0,0556 0,56 14,008 6,25 0,02

  B1.U3 0,0517 0,60 14,008 6,25 0,02

  B2.U1 0,0502 0,52 14,008 6,25 0,02

  B2.U2 0,0522 0,54 14,008 6,25 0,02

  B2.U3 Perhitungan :

  v titrasi x N HCl (0,02) x 14,008

  % N = 100%

  1000

  % Protein = %N x faktor konversi (6,25) Kode sampel Perhitungan Rata-rata

  0,56 x 0,2 x 14,008

  1,7698% %N =

  × 100% = 0,2686 %

  0,0584 x 1000

  B1.U1 % Protein = 0,2686 x 6,25 = 1,6790%

  0,58 x 0,2 x 14,008

  %N = × 100% = 0,2987%

  0,0544 x 1000

  B1.U2 % Protein = 0,2987 x 6,25 = 1,8669%

  0,56 x 0,2 x 14,008

  %N = × 100% = 0,2822%

  0,0556 x 1000

  B1.U3 % Protein = 0,2822 x 6,25 = 1,7636%

  0,60 x 0,2 x 14,008

  1,8858% %N =

  × 100% = 0,3251%

  0,0517 x 1000

  B2.U1 % Protein = 0,3251 x 6,25 = 2,0321%

  0,52 x 0,2 x 14,008

  %N = × 100% = 0,2902%

  0,0502 x 1000

  B2.U2

  0,54 x 0,2 x 14,008

  %N = × 100% = 1,8114%

  0,0522 x 1000

  B3.U3 % Protein = 0,2902 x 6,25 = 1,8114% Rata-rata Kadar Protein (%) 1,83 % 4.

   Kadar Lemak

  Batch. Kertas Kertas+ Sampel Berat labu+ Berat labu Ulangan saring (g) Sampel (g) (g) sampel kosong

  0,2280 1,2323 1,0043 33,6869 32,9368 B1.U1 B1.U2 0,2341 1,2372 1,0031 37,8126 37,1400

  0,2374 1,2401 1,0027 35,9224 35,1544 B1.U3 B2.U1 0,2378 1,2398 1,0020 35,3929 34,7416

  0,2288 1,2322 1,0034 35,1390 34,5992 B2.U2 B2.U3 0,2291 1,2321 1,0030 36,5983 35,8880

  Perhitungan : Sampel = (Berat kertas saring + sampel) – berat kertas saring

  ( + )−

  Kadar lemak = 100%

  Kode sampel Perhitungan Rata-rata

  33,6869−32,9368

  0,85% Kadar lemak =

  B1.U1 × 100% = 0,89%

  1,0043 37,8126−37,1400

  Kadar lemak = B1.U2

  × 100% = 0,79%

  1,0031 35,9224 − 35,1544

  Kadar lemak = B1.U3

  × 100% = 0,86%

  1,0027 35,3929− 34,7416

  0,73% Kadar lemak =

  B2.U1 × 100% = 0,72%

  1,0020 35,1390− 34,5992

  Kadar lemak = B2.U2

  × 100% = 0,66%

  1,0034 36,5983− 35,8880

  Kadar lemak = B3.U3

  × 100% = 0,82%

  1,0030

  Rata-rata Kadar Lemak (%) 0,79 %

5. Kadar Pati

  Batch. Berat konsentrasi Faktor Ulangan Sampel Pengencer

  B1.U1 10,0024 0,0417 125000 B1.U2 10,0024 0,0426 125000 B1.U3 10,0024 0,0421 125000 B2.U1 10,0024 0,0168 125000 B2.U2 10,0024 0,0172 125000 B2.U3 10,0024 0,0166 125000

  Perhitungan :

  0,9

  Kadar pati = 100%

  1000

  Kode sampel Perhitungan Rata-rata

  0,0417 x 125000

  47,39% Kadar pati =

  B1.U1 × 100% = 46,90%

  10,0024 x 1000 0,0426 x 125000

  Kadar pati = B1.U2

  × 100% = 47,91%

  10,0024 x 1000 0,0421 x 125000

  Kadar pati = B1.U3

  × 100% = 47,35%

  10,0024 x 1000 0,0168 x 125000

  18,97% B2.U1 Kadar pati =

  × 100% = 18,90%

  10,0024 x 1000 0,0172 x 125000

  B2.U2 Kadar pati = × 100% = 19,35%

  10,0024 x 1000 0,0166 x 125000

  B3.U3 Kadar pati = × 100% = 18,67%

  10,0024 x 1000

  Rata-rata Kadar Pati (%) 33,18 % 6.

   Gula Total

  Batch. Berat Faktor konsentrasi Ulangan Sampel Pengencer

  B1.U1 10,0001 0,0245 8000 B1.U2 10,0001 0,0244 8000 B1.U3 10,0001 0,0246 8000 B2.U1 10,0001 0,0489 8000 Perhitungan : Kadar gula total =

  100%

  1000

  Kode sampel Perhitungan Rata-rata

  0,0245 x 8000

  1,96% Gula total =

  B1.U1 × 100% = 1,96%

  10,0001 x 1000 0,0244 x 8000

  Gula total = B1.U2

  × 100% = 1,95%

  10,0001 x 1000 0,0246 x 8000

  Gula total = B1.U3

  × 100% = 1,97%

  10,0001 x 1000 0,0489 x 8000

  3,92% Gula total =

  B2.U1 × 100% = 3,91%

  10,0001 x 1000 0,0491 x 8000

  Gula total = B2.U2

  × 100% = 3,93%

  10,0001 x 1000 0,0490 x 8000

  Gula total = B3.U3

  × 100% = 3,92%

  10,0001 x 1000

  Rata-rata Kadar Gula Total (%) 2,94 % 7.

   Amilosa Batch.

  konsentrasi Ulangan

  0,0147

  B1.U1

  0,0147

  B1.U2

  0,0146

  B1.U3

  0,0162

  B2.U1

  0,0163

  B2.U2

  0,0166

  B2.U3 Perhitungan :

  100 100 × ×

  5

1 Amilosa =

  × 100%

  0,1 ×1000 Perhitungan : Berat residu yang tidak larut = Berat setelah dioven

  B1.U1 0,4090 0,8483 23,1481 23,5689 23,1538 23,1599 B1.U2 0,8339 0,8024 23,4699 24,3172 23,4772 23,4833 B1.U3 0,4371 0,8337 23,1228 23,5991 23,1568 23,1620 B2.U1 0,8189 0,8089 23,0870 23,9177 23,0969 23,0988 B2.U2 0,7495 0,7582 23,1013 23,8612 23,1061 23,1117 B2.U3 0,4942 0,8297 24,1932 24,6189 24,1192 24,1247

  1 × 0,0166 0,1 ×1000

  100

  5 ×

  100

  1 × 0,0163 0,1 ×1000

  × 100% = 32,60% B3.U3

  Amilosa =

  100

  5 ×

  100

  × 100% = 33,20% Rata-rata Amilosa (%) 31,03% 8.

  × 100% = 32,40% 32,73%

   Amilopektin

  Perhitungan : Kadar Amilopektin = Kadar Pati

   Serat Kasar Batch.

  Ulangan Berat

  Kerta (g) Berat

  Sampel (g)

  Krus kosong (g) Berat setelah dioven (g)

  Berat setelah diabu (g)

  Berat residu yang tidak larut (g)

  B2.U2 Amilosa =

  1 × 0,0162 0,1 ×1000

  Kode sampel Perhitungan Rata-rata B1.U1

  100

  Amilosa =

  100

  5 ×

  100

  1 × 0,0147 0,1 ×1000

  × 100% = 29,40% 29,33%

  B1.U2 Amilosa =

  100

  5 ×

  1 × 0,0147 0,1 ×1000

  100

  × 100% = 29,40% B1.U3

  Amilosa =

  100

  5 ×

  100

  1 × 0,0146 0,1 ×1000

  × 100% = 29,20% B2.U1

  Amilosa =

  100

  5 ×

• – Kadar Amilosa Kadar Amilopektin = 33,18
• – 31,03 = 2,15% 9.
• – Berat kertas

Kode sampel Perhitungan Rata-rata B1.U1

  Serat kasar =

  23,0988−23,0969 0,8089

  24,1247−24,1192 0,8297

  Serat kasar =

  × 100% = 0,74% B3.U3

  23,1117−23,1061 0,7582

  B2.U2 Serat kasar =

  × 100% = 0,23% 0,55%

  Serat kasar =

  23,1599−23,1538 0,8483

  × 100% = 0,62% B2.U1

  23,1620−23,1568 0,8337

  Serat kasar =

  × 100% = 0,76% B1.U3

  23,4833−23,4772 0,8024

  B1.U2 Serat kasar =

  × 100% = 0,72% 0,70%

  × 100% = 0,66% Rata-rata Serat kasar (%) 0,62%

  Lampiran . Hasil Uji Proksimat Beras Analog Oyek Tanpa Dan Dengan Kacang Hijau 1. Kadar Air

  B2.U3 12,4031 13,4033 1,0002 13,309 0,9059 9,43 Beras analog oyek 5 hari

  B2.U3 13,4447 14,445 1,0003 14,352 0,9073 9,30

  Beras analog oyek 4 hari

  B1.U1 12,4854 13,4859 1,0005 13,3974 0,9120 8,85

  B1.U2 13,8941 14,8978 1,0037 14,8101 0,9160 8,74

  B1.U3 12,4034 13,4073 1,0039 13,3187 0,9153 8,83

  B2.U1 12,4849 13,4856 1,0007 13,3938 0,9089 9,17

  B2.U2 13,8938 14,8946 1,0008 14,7984 0,9046 9,61

  B1.U1 15,8188 16,8197 1,0009 16,7369 0,9181 8,27

  B2.U1 12,8627 13,863 1,0003 13,7483 0,8856 11,47

  B1.U2 12,358 13,3596 1,0016 13,2754 0,9174 8,41

  B1.U3 17,2327 18,2329 1,0002 18,1422 0,9095 9,07

  B2.U1 15,8175 16,8177 1,0002 16,7243 0,9068 9,34

  B2.U2 12,3575 13,358 1,0005 13,263 0,9055 9,50

  B2.U3 17,232 18,2324 1,0004 18,136 0,9040 9,64 Beras analog oyek kc. Hijau

  B1.U1 11,0626 12,0635 1,0009 11,9693 0,9067 9,41

  B1.U2 11,6089 12,6163 1,0074 12,5203 0,9114 9,53 B1.U3

  B2.U2 15,9385 16,9393 1,0008 16,844 0,9055 9,52

  B1.U3 13,4466 14,4497 1,0031 14,3655 0,9189 8,39

  Perhitungan : Sampel = (berat boto l+ sampel) – berat botol kosong Sampel Akhir = berat botol oven konstan - berat botol kosong Kadar air (%) =

  Beras analo oyek 2 hari

  berat sampel − berat sampel akhir berat sampel

  × 100% Sampel Batch.

  Ulangan Botol kosong (g)

  Botol+ Sampel (g)

  Sampel (g)

  Botol oven konstan (g) Sampel akhir

  (g) Kadar air %bb

  B1.U1 13,8560 14,8619 1,0059 14,7727 0,9167 8,87

  B1.U2 15,9365 16,9372 1,0007 16,8545 0,9180 8,26

  B1.U2 15,6466 16,6499 1,0033 16,5576 0,9110 9,20

  B1.U3 12,9648 13,9671 1,0023 13,8779 0,9131 8,90

  B2.U1 13,8544 14,8551 1,0007 14,7602 0,9058 9,48

  B2.U2 15,6456 16,6495 1,0039 16,5515 0,9059 9,76

  B2.U3 12,9649 13,9661 1,0012 13,8549 0,8900 11,11

  Beras analog oyek 3 hari

  B1.U1 12,8629 13,8789 1,0160 13,7904 0,9275 8,71

  11,5180 12,5286 1,0106 12,4325 0,9145 9,51 11,0624 12,0653 1,0029 11,9678 0,9054 9,72 B2.U3 11,5175 12,5188 1,0013 12,4205 0,9030 9,82

  Beras analog oyek kc. Hijau 3 hari

  B1.U1 12,8609 13,8683 1,0074 13,7768 0,9159 9,08 B1.U2

  13,5745 14,5763 1,0018 14,4853 0,9108 9,08 B1.U3 13,4466 14,4497 1,0031 14,3655 0,9189 8,39 B2.U1

  12,8595 13,8597 1,0002 13,7648 0,9053 9,49 B2.U2 13,5745 14,5752 1,0007 14,4800 0,9055 9,51 B2.U3

  12,1149 13,115 1,0001 13,0172 0,9023 9,78 Beras analog oyek kc. Hijau 4 hari

  B1.U1 11,6064 12,609 1,0026 12,5204 0,9140 8,84 B1.U2

  14,153 15,1545 1,0015 15,0632 0,9102 9,12 B1.U3 13,5844 14,585 1,0006 14,4933 0,9089 9,16 B2.U1

  11,6062 12,6069 1,0007 12,5167 0,9105 9,01 B2.U2 14,1497 15,1503 1,0006 15,0616 0,9119 8,86 B2.U3

  13,5829 14,583 1,0001 14,4932 0,9103 8,98 Beras analog oyek kc. Hijau 5 hari

  B1.U1 12,3957 13,3986 1,0029 13,3031 0,9074 9,52 B1.U2

  10,8335 11,8351 1,0016 11,7437 0,9102 9,13 B1.U3 15,7565 16,7586 1,0021 16,6672 0,9107 9,12 B2.U1

  12,0331 13,0331 1,0000 12,9433 0,9102 8,98 B2.U2 10,8332 11,8334 1,0002 11,7385 0,9053 9,49 B2.U3

  15,7562 16,757 1,0008 16,6616 0,9054 9,53