Outlier detection in UV/Vis spectrophotometric data

Lepot, Mathieu; Aubin, Jean Baptiste; Clemens, F.H.L.R.; Mašić, Alma

doi:10.1080/1573062x.2017.1280515

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…The accuracy and robustness require a local calibration. Taking into account the local specifications of the water matrices, samples are collected, measured with the special device and concentration are measured with laboratory analysis [4,5].…”

Section: Introductionmentioning

confidence: 99%

Determination Characteristic and Classification the Types of Orange Using UV-Vis Spectrophotometer by K-Nearest Neighbor Algorithm

Pratama¹,

Gunawan²,

Suyanto³

2019

I2M

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It has been researched at Laboratorioum Terpadu Faculty of Science and Mathematics. The purpose of this study is determining to distinguish in characteristic between sweet orange and sour orange, it makes sure wavelength and absorbance using UV-Vis Spectrophotometer. Furthermore, it is also determining classification between sweet orange and sour orange by predicting between actual data and predictive data. The method used is K-Nearest Neighbor algorithm using MATLAB 2015. Sweet orange and sour orange are researched for their characteristic to be analyzed whether they have significant differences in wavelength and absorbance. The KNN algorithm is used to see its ability in classification to predict sweet orange and sour orange data from actual data. Through this study, it is found that resulting characteristic of sweet oranges and acid oranges has a different, it can be seen based on forms wavelength and absorbance. Sweet oranges and acid oranges have they own characteristic. On the classification, prediction data results showing that 23 correct data from 40 actual data obtained a percentage of 67.5 % by using K-Nearest Neighbor. The finding of this research may serve as reference. The finding of this study may serve as reference for other researchers to be developed further.

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Section: Introductionmentioning

confidence: 99%