1. Budi Hastuti, S.Pd., M.Si.

2. INTRODUCTION

3.  Two step analysis: 1. Identify  Qualitative Analysis 2. Estimation  Quantitative Analysis Method  Classical / conventional  Modern Analytical scale  Macro, semimakro  Ultramikro,Micro  Submikro

4.  ANALYSIS covers 3 aspects comprehensively: 1. Data collection 2. Data processing, interpretation 3. Judgement, decision making / conclusions

5.  Analytical Chemystry is a science that identify the types of components in a sample (qualitative analysis) and determine the relative amounts of each component (quantitative analysis).  Generally, phase separation is necessary to isolate the components in the samples analyzed.  The method used distinguished role in 2 groups namely: Classical Methods Instrumental Methods

6.  CLASSICAL METHODS - also called wet method 1. Separation of analytes - extraction, distillation, precipitation (precipitation), filtration (filtering), etc.. 2. Qualitative Analysis - boiling point, freezing point, color, odor, density, reactivity, refractive index, etc.. 3. Quantitative Analysis - gravimetric and volumetric analysis.

7. The classic analyticalThe modern analytical  Long way since the beginning of analytical chemistry  Dispensable complicated tools  sufficient sample quantaty is needed (macro, semi-macro)  Based on chemical reactions and the Stoichiometry equation  based of matter-matter interactions  A new way, consistent development of science and technology  It takes more complicated contraption  small sample size (micro, ultramikro, submikro)  Based on the measurement of physical quantities of non stoichiometry  Based of energy-matter interactions

8.  Sensitive  Fast  Selective and specific  Objective  Often non-destructive  Easily automated

9.  expensive tools  Utilization and complexmaintenance  Need a special technician  Need additional tools, calibration and standardization of cheese (sometimes difficult)  needs a good environment

10.  Instrumental Method exploit the physical properties of an analyte to obtain information, both qualitative and quantitative.  Separation of analytes - Can be done in 2 ways: a. Physical separation: - Chromatography - Electrophoresis b. Spectroscopic separation: isolate the signal that appears in spectroscophy

11.  Instrumental Method 1. Separation of analytes 2. Qualitative Analysis * X-Ray Spectroscopy * Infrared Spectroscopy (IR) * mass spectroscopy (MS) * nuclear magnetic spectroscopy (NMR) 3. Quantitive Analysis * UV-Vis Spectroscopy * Atomic absorption & emission spectroscopy (AAS and AES) * mass spectroscopy (MS) * Conductivity (pH)

12.  Type method of Instrumental

14.  To determine the appropriate analytical method (the best), the analyst should ask the following things: a. Is accuracy required? b. How many samples are available? c. How much range of concentrations found in the sample? d. Are there any components in the sample that cause interference? e. How physical and chemical properties of the matrix contained in the sample? f. How many samples to be analyzed?

15. Performance characteristics  Precision  Absolute standard deviation  Relative standard deviation  Coefficient of variation  Variance  Accuracy/Bias  Absolute systematic error  Relative systematic error  Sensitivity  Calibration  Analytical  Detection Limit  Blank plus three times Std. Dev. of blank  Limit of Linearity (LOL)  Selectivity  Effects of interferences  Coefficient of Selectivity The criteria used to compare several analytical methods

16. The other criteria that need to be considered in the selection of analytical methods: a Velocity analysis b Convenience analysismethods c Operator skill level d Cost and availability of equipment (instruments) e Cost of analysis every sample

17. Performance characteristics 1. PRECISION Measure reproducibility of a determination set a) Absolute standard deviation (s) 1 )( 2 _ 1      N xx s N i i _  x s RSD b) Relative standard deviation (RSD) %100 _  x s CV c) Coefficient of variance (CV) /  nsSE c) Standard error of mean (SE)

18. Performance characteristics 2. ACCURACY (BIAS) Measure the error of an analytical method. a) Absolute bias (E a ) a) Persen bias (% error)

19. Performance characteristics 3. SENSITIVITY The ability to distinguish effect of increasing concentration on instrument response. S = signal or instrument response S bl = signal from blank sample c = sample concentration m = calibration sensitivity (slope of calibration curve) a)Calibration sensitivity (m)  S m1 CC  S m2 b)Analytical sensitivity (  )  = analytical sensitivity m = calibration sensitivity s S = std. dev. in signal measurement

20. Performance characteristics 4. DETECTION LIMIT Concentration / minimum analyte mass that still can be detected (still can be distinguished from the noise) by a analysis method based on certain confidence level (usually 95%) a)Minimum detectable signal (S m ) S m = minimum detectable signal S avg,bl = average signal of the blank s bl = standard deviation in the blank signal k = multiple of variation in the blank signal The analytical signal must be larger than the blank signal (S avg,bl ) by some factor (k) of the standard deviation in the blank (s bl ). k is usually set to a value of three. The analytical signal must be larger than the blank signal (S avg,bl ) by some factor (k) of the standard deviation in the blank (s bl ). k is usually set to a value of three. b)Minimum detectable concentration (c m ) Limit of Detection (LOD) Limit of Detection (LOD) c m = minimum detectable concentration m = slope of the calibration curve Expressed in terms of s bl Expressed in terms of s bl

21. Performance characteristics 5. SELECTIVITY Degree an analytical method is free from interference that contained on the sample matrix S cAcA S bl m A = slope m B = slope m C = slope cBcB cCcC )( / /,, blCACBABAA, ACAC,ABAB CCBBAA Sckckcm S mmk mmk ScmcmcmS     k is the selectivity coefficient K value ranging from 0 (not selective) up to a certain figure. Increase k, the methods more selective