Akurasi

Menurut ISO, akurasi didefinisikan sebagai kesesuaian antara hasil analisis dengan nilai benar analit (atau nilai acuan analit yang dapat diterima).

Akurasi dapat ditentukan melalui bebegai cara :

  • Pemakaian CRM
  • Perbandingan dengan metode lain
  • Standar Adisi

Nilai benar dari analit diperoleh dari nilai CRM yang digunakan. Biasanya CRM punya sertifikat maka itulah nilai benarnya. Penetapan akurasi menganalisis perbedaan antara hasil analis dengan nilai benar. Akurasi dihitung dengan rumus berikut :

Akurasi

Daftar Pustaka

Modul “Kursus Pengolahan Data Hasil Validasi Metode Analisis Kimia” Bandung 19 – 23 Juni 2006 RCChem Learning Centre

Uncertainties in Analytical Processes

In order to identify the possible sources of uncertainty in an analytical procedure it is helpful to break down the analysis into a set of generic steps:

1. Sampling

– Homogeneity.

– Effects of specific sampling strategy (e.g. random, stratified random,    proportional etc.)

– Effects of movement of bulk medium (particularly density selection)

– Physical state of bulk (solid, liquid, gas)

– Temperature and pressure effects.

– Does sampling process affect composition? E.g. differential adsorption in sampling system.

2. Sample preparation

– Homogenisation and/or sub-sampling effects.

– Drying.

– Milling.

– Dissolution.

– Extraction.

– Contamination.

– Derivatisation (chemical effects)

– Dilution errors.

– (Pre-)Concentration.

– Control of speciation effects

3. Presentation of Certified Reference Materials to the measuring system

– Uncertainty for CRM.

– CRM match to sample

4. Calibration of Instrument

– Instrument calibration errors using a Certified Reference Material.

– Reference material and its uncertainty.

– Sample match to calibrant

– Instrument precision

5. Analysis (data acquisition)

– Carry-over in auto analysers.

– Operator effects, e.g. colour blindness, parallax, other systematic errors.

– Interferences from the matrix, reagents or other analytes.

– Reagent purity.

– Instrument parameter settings, e.g. integration parameters

– Run-to-run precision

6. Data processing

– Averaging.

– Control of rounding and truncating.

– Statistics.

– Processing algorithms (model fitting, e.g. linear least squares).

7. Presentation of results

– Final result.

– Estimate of uncertainty.

– Confidence level.

8. Interpretation of results

– Against limits/bounds.

– Regulatory compliance.

– Fitness for purpose.

Reference

EURACHEM/CITAC Guide Quantifying Uncertainty in Analytical Measurement Third Edition Editors S L R Ellison (LGC, UK) A Williams (UK)