Appendix 1. The result of normality with Kolmogorov-Smirnov method and descriptive

Similar documents
KUESIONER PENELITIAN. No. Responden: Kepada Yth. Saudara/i di tempat. Dengan hormat,

Saya, selaku Ketua Paguyuban Lansia Gereja Katolik Kelahiran Santa. Perawan Maria Surabaya, menyatakan bahwa mahasiswa bernama Dewi Setiawati

Descriptive Statistics

kurva standar betakaroten

Correlations. Notes. Output Created Comments 04-OCT :34:52

unadjusted model for baseline cholesterol 22:31 Monday, April 19,

One-Way ANOVA Source Table J - 1 SS B / J - 1 MS B /MS W. Pairwise Post-Hoc Comparisons of Means

MANOVA is an extension of the univariate ANOVA as it involves more than one Dependent Variable (DV). The following are assumptions for using MANOVA:

Solutions exercises of Chapter 7

Z score indicates how far a raw score deviates from the sample mean in SD units. score Mean % Lower Bound

PERBANDINGAN LEBAR ENAM GIGI ANTERIOR RAHANG ATAS DENGAN JARAK INTERKANTAL DAN LEBAR INTERALAR PADA MAHASISWA INDONESIA FKG USU ANGKATAN

SPSS Guide For MMI 409

N J SS W /df W N - 1

Item-Total Statistics. Corrected Item- Cronbach's Item Deleted. Total

ANALISIS BIVARIAT DATA NUMERIK DAN NUMERIK Uji Korelasi dan Regresi

Levene's Test of Equality of Error Variances a

Three Factor Completely Randomized Design with One Continuous Factor: Using SPSS GLM UNIVARIATE R. C. Gardner Department of Psychology

T-Test QUESTION T-TEST GROUPS = sex(1 2) /MISSING = ANALYSIS /VARIABLES = quiz1 quiz2 quiz3 quiz4 quiz5 final total /CRITERIA = CI(.95).

Multiple Comparisons

Data Analysis. Associate.Prof.Dr.Ratana Sapbamrer Department of Community Medicine, Faculty of Medicine Chiang Mai University

Introduction and Descriptive Statistics p. 1 Introduction to Statistics p. 3 Statistics, Science, and Observations p. 5 Populations and Samples p.

SPSS Output. ANOVA a b Residual Coefficients a Standardized Coefficients

Chapter 8 (More on Assumptions for the Simple Linear Regression)

Handout 1: Predicting GPA from SAT

Glossary. The ISI glossary of statistical terms provides definitions in a number of different languages:

Prepared by: Prof. Dr Bahaman Abu Samah Department of Professional Development and Continuing Education Faculty of Educational Studies Universiti

Chapter 7 Factorial ANOVA: Two-way ANOVA

M A N O V A. Multivariate ANOVA. Data

BST 203/3 Population and Community Ecology [Ekologi Populasi dan Komuniti]

This is a Randomized Block Design (RBD) with a single factor treatment arrangement (2 levels) which are fixed.

Testing for Normality

SAS Procedures Inference about the Line ffl model statement in proc reg has many options ffl To construct confidence intervals use alpha=, clm, cli, c

An Analysis of College Algebra Exam Scores December 14, James D Jones Math Section 01

Statistical Methods. by Robert W. Lindeman WPI, Dept. of Computer Science

Regresi Logistik II. (Peubah Bebas : Kategorik) Dr. Kusman Sadik, M.Si Program Studi Pascasarjana Departemen Statistika IPB, 2018/2019

Multiple Regression. More Hypothesis Testing. More Hypothesis Testing The big question: What we really want to know: What we actually know: We know:

Stevens 2. Aufl. S Multivariate Tests c

EXST7015: Estimating tree weights from other morphometric variables Raw data print

Testing for Normality

ANALYSIS OF VARIANCE OF BALANCED DAIRY SCIENCE DATA USING SAS

Comparing t Test, Significance Test, and Criteria for Item Selection Method: A Simulation Study

Univariate Analysis of Variance

STATISTIKA INDUSTRI 2 TIN 4004

Lecture 06. DSUR CH 05 Exploring Assumptions of parametric statistics Hypothesis Testing Power

SCES2260 : KAEDAH SPEKTROSKOPI DALAM KIMIA ORGANIK SPECTROSCOPIC METHODS IN ORGANIC CHEMISTRY

SPSS LAB FILE 1

Psychology 282 Lecture #4 Outline Inferences in SLR

Psy 420 Final Exam Fall 06 Ainsworth. Key Name

ESP 178 Applied Research Methods. 2/23: Quantitative Analysis

The entire data set consists of n = 32 widgets, 8 of which were made from each of q = 4 different materials.

Degrees of freedom df=1. Limitations OR in SPSS LIM: Knowing σ and µ is unlikely in large

ANCOVA. Psy 420 Andrew Ainsworth

Difference in two or more average scores in different groups

Cheat Sheet: ANOVA. Scenario. Power analysis. Plotting a line plot and a box plot. Pre-testing assumptions

The Difference in Proportions Test

MAT 223 DIFFERENTIAL EQUATIONS I [Persamaan Pembezaan I]

Using SPSS for One Way Analysis of Variance

Cheat Sheet: factorial ANOVA

4.1. Introduction: Comparing Means

Basics on t-tests Independent Sample t-tests Single-Sample t-tests Summary of t-tests Multiple Tests, Effect Size Proportions. Statistiek I.

Basics of Experimental Design. Review of Statistics. Basic Study. Experimental Design. When an Experiment is Not Possible. Studying Relations

Regression ( Kemampuan Individu, Lingkungan kerja dan Motivasi)

Ø Set of mutually exclusive categories. Ø Classify or categorize subject. Ø No meaningful order to categorization.

(Kertas ini mengandungi 6 soalan dalam 9 halaman yang dicetak) (This question paper consists of 6 questions on 9 printed pages)

Basic Statistical Analysis

Biological Applications of ANOVA - Examples and Readings

Chapter 13 Correlation

Frequency Distribution Cross-Tabulation

DETAILED CONTENTS PART I INTRODUCTION AND DESCRIPTIVE STATISTICS. 1. Introduction to Statistics

What Does the F-Ratio Tell Us?

TABLES AND FORMULAS FOR MOORE Basic Practice of Statistics

The independent-means t-test:

Area1 Scaled Score (NAPLEX) .535 ** **.000 N. Sig. (2-tailed)

Last Lecture. Distinguish Populations from Samples. Knowing different Sampling Techniques. Distinguish Parameters from Statistics

Assessing the relation between language comprehension and performance in general chemistry. Appendices

TOPIC 9 SIMPLE REGRESSION & CORRELATION

ANOVA continued. Chapter 10

Contents. Acknowledgments. xix

R in Linguistic Analysis. Wassink 2012 University of Washington Week 6

Independent Samples ANOVA

The Empirical Rule, z-scores, and the Rare Event Approach

5.3 Three-Stage Nested Design Example

PSY 216. Assignment 12 Answers. Explain why the F-ratio is expected to be near 1.00 when the null hypothesis is true.

Punctuated Equilibrium and Institutional Friction in Comparative Perspective

PLS205 Winter Homework Topic 8

Tastitsticsss? What s that? Principles of Biostatistics and Informatics. Variables, outcomes. Tastitsticsss? What s that?

Non-Parametric Two-Sample Analysis: The Mann-Whitney U Test

ANOVA continued. Chapter 10

MAT111 Linear Algebra [Aljabar Linear]

Model Linear Terampat (Generalized Linear Model / GLM) Dr. Kusman Sadik, M.Si Departemen Statistika IPB, 2017/2018

DESIGNING EXPERIMENTS AND ANALYZING DATA A Model Comparison Perspective

Two-Way ANOVA. Chapter 15

Chapter Goals. To understand the methods for displaying and describing relationship among variables. Formulate Theories.

Practical Statistics for the Analytical Scientist Table of Contents

(Kertas soalan ini mengandungi 6 soalan dalam 9 halaman yang dicetak) (This question paper consists of 6 questions on 9 printed pages)

" M A #M B. Standard deviation of the population (Greek lowercase letter sigma) σ 2

Self-Assessment Weeks 6 and 7: Multiple Regression with a Qualitative Predictor; Multiple Comparisons

DATA ANALYSIS. Faculty of Civil Engineering

MAT 100 Foundation Mathematics [Asas Matematik]

One-Way ANOVA. Some examples of when ANOVA would be appropriate include:

Transcription:

Appendix 1. The result of normality with Kolmogorov-Smirnov method and descriptive Kolmogorov-Smirnov(a) Tests of Normality Shapiro-Wilk Statistic df Sig. Statistic df Sig. VISKO.83 7.(*).969 7.76 AW.3 7.63.913 7 KA. 7.82.97 7 5 JML_MO. 7.77.968 7.71 * This is a lower bound of the true significance. a Lilliefors Significance Correction Descriptives AW Statistic Std. Error Mean.875 8267 95% Confidence Lower Bound Interval for Mean Upper Bound.831.86399 KA 5% Trimmed Mean.878 Median.836 Variance 5 Std. Deviation.699 Minimum.75 Maximum.95 Range. Interquartile Range.13 Skewness.156.287 Kurtosis -1.8.566 Mean 1.31825.91299 95% Confidence Lower Bound Interval for Mean Upper Bound.33813 2.29836 5% Trimmed Mean 1.232635 Median.7325 Variance.896 Std. Deviation.152 Minimum 35.12 Maximum 9.567 Range 1.583 Interquartile Range 7.325 Skewness.33.287 Kurtosis -1.83.566 35

VISKO Mean 63.571.882 95% Confidence Lower Bound Interval for Mean 31.352 Upper Bound 95.777 5% Trimmed Mean 63.8889 Median 5 Variance 18.596 Std. Deviation 13.776 Minimum Maximum 7 Range 5 Interquartile Range Skewness.71.287 Kurtosis -.799.566 JML_MO Mean.98.18991 95% Confidence Lower Bound Interval for Mean.5691 Upper Bound 5.3269 5% Trimmed Mean.89 Median.26 Variance 2.525 Std. Deviation 1.58888 Minimum 3 Maximum 9. Range 6. Interquartile Range 1.95 Skewness 1.29.287 Kurtosis.159.566 36

1 Appendix 2. The result of chemical water activity analysis Univariate Analysis of Variance Between-Subjects Factors Value Label N Kons_Jahe 1 % 1 2.5% 1 3 1 1 1.5% 1 5 2% 1 Umur_sim 1 2 3 5 6 Descriptive Statistics Dependent Variable: AW Kon_Jahe Umur_sim Mean Std. Deviation N %.76 5657 2 1.789 2828 2 2.828 23 2 3.858 23 2.899 23 2 5.9385 2121 2 6.95 2828 2.8679.7237 1.5%.76 5657 2 1.7865 2121 2 2.8215 3536 2 3.863 2828 2.8925 95 2 5.9355 3536 2 6.95 2828 2.85857.7129 1 1.7555 2121 2 1.7775 2121 2 2.8115 3536 2

2 1.5% 2% 3.836 11 2.88 2828 2 5.9275 3536 2 6.995 2121 2.8821.7899 1.75 11 2 1.769 2828 2 2.815 95 2 3.827 23 2.868 23 2 5.919 11 2 6.97 11 2.836.71386 1.75 2 1.765 11 2 2.7935 9192 2 3.895 3536 2.8 5657 2 5.985 2121 2 6.9385 2121 2.82957.68528 1.7555 553 1.777.58 2.811.13919 3.8387.22.8763.21536 5.9258.11755 6.976 5.875.699 7 Tests of Between-Subjects Effects Dependent Variable: AW Type III Sum of Mean Source Squares df Square F Sig. Corrected Model.33(a) 3. 719.711 Intercept 373219 5.278 1 5.278.83 Kon_Jahe 9 2 17.65 Umur_Sim 3928.9.318 6.53 7 Kon_Jahe * Umur_sim 3 2 8.365 Error 35 1.37E-5 5.68 7 Corrected.33 69 a R Squared =.999 (Adjusted R Squared =.997)

3 Estimated Marginal Means Grand Mean Dependent Variable: AW 95% Confidence Interval Mean Std. Error Lower Bound Upper Bound.88.87.88 Post Hoc Tests Homogeneous Subsets Duncan a,b 2% 1.5% 1.5% % Sig. AW N 1 2 3 1.82957 1.836 Subset 1.8821 1.85857 1.8679.119 Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 1.37E-5. a. Uses Harmonic Mean Sample Size =. b. Alpha =.5.

Homogeneous Subsets Duncan a,b 1 2 3 5 6 Sig. AW N 1 2 3 5 6 7.7555.777.811.8387.8763.9258.976 Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 1.37E-5. a. Uses Harmonic Mean Sample Size =. b. Alpha =.5. Subset

Appendix 3. The result of chemical (moisture content) analysis Univariate Analysis of Variance Between-Subjects Factors 1 2 3 5 1 2 3 5 6 Value Label N % 1.5% 1 1 1 1.5% 1 2% 1

Descriptive Statistics Dependent Variable: KA %.5% 1 1.5% 2% 1 2 3 5 6 1 2 3 5 6 1 2 3 5 6 1 2 3 5 6 1 2 3 5 6 1 2 3 5 6 Mean Std. Deviation N 36.6993 8853 2 38.6595.15856 2.3355.9538 2 2.5575.1177333 2 5.5585.386 2 6.5.291823 2 9.3975.236887 2 2.83.3877 1 36.33175.215668 2 38.2585.231296 2 39.7813 3391 2 1.27795.899 2.5983.3221 2 6.37.111723 2 8.1915 5333 2 2.125129.2293897 1 36.63935.271711 2 38.888.1115815 2 39.7385.622 2 1.582325.8529 2 3.222725.86 2 6.33525.6877 2 8.5333.26337 2 2.12639.712753 1 35.229 2 36.9 2 37.6 2 39.18 2.8279 2.2925 2 5.6326 2 39.93631 3.7237152 1 35.76.9783 2 36.33925.1763 2 37.59875.768625 2 38.5675.125158 2.7325.2655 2 3.9683.562857 2.873.125922 2 39.5855 3.671356 1 35.989.752362 37.8585 1.537958 38.9772 1.2655.633235 1.59931 2.982125 2.627117 5.515 1.5327 7.32528 1.858 1.31825.152 7

Dependent Variable: KA Source Corrected Model Intercept * Error Corrected Tests of Between-Subjects Effects Type III Sum of Squares df Mean Square F Sig. 15.368 a 3 3.276 25.6 11953.8 1 11953.8 8871369 118.6 29.552 2193.758 31.57 6 171.99 12761.73 15.75 2.65 8.579.71 35.13 1669.656 7 15.8 69 a. R Squared = (Adjusted R Squared =.999) Estimated Marginal Means Dependent Variable: KA Grand Mean 95% Confidence Interval Mean Std. Error Lower Bound Upper Bound 1.318.1 1.29 1.36 Post Hoc Tests Homogeneous Subsets Duncan a,b 2% 1.5%.5% 1 % Sig. KA N 1 2 3 1 39.5855 1 39.93631 Subset 1 2.125129 1 2.12639 1 2.83.692 Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) =.13. a. Uses Harmonic Mean Sample Size =. b. Alpha =.5.

Homogeneous Subsets Duncan a,b 1 2 3 5 6 Sig. KA N 1 2 3 5 6 7 35.989 37.8585 38.9772.633235 2.982125 5.515 7.32528 Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) =.13. a. Uses Harmonic Mean Sample Size =. b. Alpha =.5. Subset

Appendix. The result of physical analysis Univariate Analysis of Variance Between-Subjects Factors 1 2 3 5 1 2 3 5 6 Value Label N % 1.5% 1 1 1 1.5% 1 2% 1

Descriptive Statistics Dependent Variable: VISKO %.5% 1 1.5% 2% 1 2 3 5 6 1 2 3 5 6 1 2 3 5 6 1 2 3 5 6 1 2 3 5 6 1 2 3 5 6 Mean Std. Deviation N 675 35.3553 2 562.5 17.67767 2 5 2 5 2 375 35.3553 2 325 35.3553 2 237.5 17.67767 2 6.286 13.73358 1 675 35.3553 2 575 35.3553 2 525 35.3553 2 37.5 17.67767 2 37.5 17.67767 2 325 35.3553 2 212.5 17.67767 2 55.3571 15.37727 1 675 35.3553 2 55 7.768 2 55 2 25 35.3553 2 2 35 2 262.5 17.67767 2 58.9286 137.136 1 675 35.3553 2 575 35.3553 2 87.5 17.67767 2 5 2 12.5 17.67767 2 375 35.3553 2 287.5 17.67767 2 66.71 125.1 1 7 2 6 2 525 35.3553 2 512.5 17.67767 2 25 35.3553 2 375 35.3553 2 3 2 91.71 132.171 1 68 25.81989 572.5 3.2581 517.5 28.98755 55 3.9629 29.369 35 33.33333 26 35.762 63.571 13.776 7

Dependent Variable: VISKO Source Corrected Model Intercept * Error Corrected Tests of Between-Subjects Effects Type III Sum of Squares df Mean Square F Sig. 122682.13 a 3 3673 6.979 152892.9 1 152892.86 1959.7 35.71 8.929 5.221 2 1188982.13 6 1983.69 258.7 2.286 2 89.35 1.5.33 26875 35 767.857 29625. 7 1253357.13 69 a. R Squared =.979 (Adjusted R Squared =.958) Estimated Marginal Means Grand Mean Dependent Variable: VISKO 95% Confidence Interval Mean Std. Error Lower Bound Upper Bound 63.571 3.312 56.88 7.295 Post Hoc Tests Homogeneous Subsets Duncan a,b %.5% 1 1.5% 2% Sig. VISKO N 1 2 1 6.286 1 55.3571 1 58.9286 1 66.71 Subset 1 91.71.9 Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 767.857. a. Uses Harmonic Mean Sample Size =. b. Alpha =.5.

Homogeneous Subsets Duncan a,b 6 5 3 2 1 Sig. VISKO N 1 2 3 5 6 7 26 35 55 517.5 572.5 68 Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 767.857. a. Uses Harmonic Mean Sample Size =. b. Alpha =.5. Subset

Appendix 5. The result of microbiological analysis Univariate Analysis of Variance Between-Subjects Factors 1 2 3 5 1 2 3 5 6 Value Label N % 1.5% 1 1 1 1.5% 1 2% 1 Descriptive Statistics Dependent Variable: JML_MO Mean Std. Deviation N % 3.985.2121 2 1.15.2121 2 2.26.2828 2 3 5.27.11 2 5.88.885 2 5 7.25.2121 2 6 9.75.3536 2 5.7 1.853 1.5% 3.86.11 2 1..11 2 2..2828 2 3.765.57 2 5.285.95 2 5 7.3.885 2 6 8.25.27577 2 5.7 1.78 1 1 3.55.5657 2 1 3.65.3777 2 2.95 77 2 3.28.885 2 5.55.2121 2 5 5.37.11 2 6 7.285.3536 2.786 1.26375 1 1.5% 3 2 1 3.55.3536 2 2 3.835.95 2 3.95 77 2

2%.8.29698 2 5 5.25 77 2 6 7.29.23 2.557 1.372 1 3 2 1 3 2 2 3.57.23 2 3 3.99.11 2.26.2828 2 5 5..19799 2 6 7.5.636 2.35 1.3993 1 3.79.3895 1 3.663.17 2 3.98.265 3.8.5352 5.58.57253 5 6.136 1.11531 6 7.836.8266.98 1.58888 7 Dependent Variable: JML_MO Tests of Between-Subjects Effects Source Type III Sum of Squares df Mean Square F Sig. Corrected Model 173.57(a) 3 5.3 26.62 Intercept 1713.789 1 1713.789 87336.379 * 6.9 2.259 13.185.83 5.21 255.862 17.215 6 2.536 125.37 Error.687 35. 1887.983 7 Corrected 17.19 69 a R Squared =.996 (Adjusted R Squared =.992) Estimated Marginal Means Dependent Variable: JML_MO Grand Mean 95% Confidence Interval Mean Std. Error Lower Bound Upper Bound.98.17.91.982 Post Hoc Tests

Homogeneous Subsets JML_MO Duncan Subset N 1 2 3 5 2% 1.35 1.5% 1.557 1 1.786.5% 1 5.7 % 1 5.7 Sig. Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) =.. a Uses Harmonic Mean Sample Size =. b Alpha =.5.

Homogeneous Subsets JML_MO Duncan Subset N 1 2 3 5 6 7 3.79 1 3.663 2 3.98 3.8 5.58 5 6.136 6 7.836 Sig. Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) =.. a Uses Harmonic Mean Sample Size =. b Alpha =.5.

Appendix 6. Questioner form Nama : Umur : Tanggal : (P/L) Berkaitan dengan penelitian yang saya lakukan tentang penambahan jahe pada produk selai, maka saya meminta bantuan saudara/i untuk mengisi kuesioner dibawah ini. Dan saya mengucapkan terima kasih atas kesediaan saudara/i mengisi kuesioner tersebut. Kuesioner Mohon mengisi tabel dibawah ini yang sesuai menurut anda, setelah sampel selai diberikan. Sampel Rasa Tekstur Warna Aroma Overall 121 26 357 68 567 Kriteria pengisian nilai: 1. sangat suka 2. suka 3. kurang suka. tidak suka 5. sangat tidak suka TERIMA KASIH Appendix 7. The result of sensory analysis

Table 7. Organoleptic analysis Percentage the addition of ginger on pumpkin jam Parameter Acceptance scale %.5% 1% 1.5% 2% Taste Very like Like Less like Unlike Very unlike 28 8 8 32 2 8 28 2 32 2 28 2 score 2 26 252 272 336 Texture Very like Like Less like Unlike Very unlike 28 8 8 56 12 52 36 8 52 2 28 28 score 212 22 28 3 Color Very like Like Less like Unlike Very unlike 12 8 68 8 2 56 32 2 8 28 score 176 276 Aroma Very like Like Less like Unlike Very unlike 8 56 12 36 28 2 12 2 12 28 28 12 score 28 268 2 3 Overall Very like Like Less like Unlike Very unlike 12 56 8 12 36 32 8 2 32 32 score Overall of score 236 118 2 118 228 118 26 13 356 1732 The example of calculation sensory analysis (taste of ginger %): score = (x %x1)+(11x %x2)+(x %x3)+(11x %x)+(x %x5) 25 25 25 25 25 = 2

Appendix 8. The result of correlations factor Correlations Correlations AW KA VISKO JML_MO AW KA VISKO JML_MO Pearson Correlation 1 -.6 -.299(*).6 -.332(**) Sig. (2-tailed)..9.12.38 5 N 7 7 7 7 7 7 Pearson Correlation 1.976(**).935(**) -.968(**).86(**) Sig. (2-tailed). N 7 7 7 7 7 7 Pearson Correlation -.6.976(**) 1.97(**) -.95(**).99(**) Sig. (2-tailed).9. N 7 7 7 7 7 7 Pearson Correlation -.299(*).935(**).97(**) 1 -.93(**).926(**) Sig. (2-tailed).12. N 7 7 7 7 7 7 Pearson Correlation.6 -.968(**) -.95(**) -.93(**) 1 -.87(**) Sig. (2-tailed).38. N 7 7 7 7 7 7 Pearson Correlation -.332(**).86(**).99(**).926(**) -.87(**) 1 Sig. (2-tailed) 5. N 7 7 7 7 7 7 * Correlation is significant at the.5 level (2-tailed). ** Correlation is significant at the.1 level (2-tailed).