Abstract

The necessity for point-of-care, low-cost devices for early screening are an important issue at hand. Several methods to identify liquids using their spectrum have been analyzed and liquids with small differences in their molecules have been identified. Methods of dimensionality reduction, such as principal component analysis, are used to check the clustering of different liquids. In this paper, an optical instrumentation development is approached, using six wavelength values of the visible light spectrum, to identify six different liquid samples, urine, drinking water, vanilla flavoring liquid, Surabaya's tap water, and yellow food color. After a normalization process and by using a principal component analysis dimensionality reduction from six to two dimensions, 97.61 percent of the information was captured, and the system was able to differentiate all five samples into different clusters.

Original languageEnglish
Title of host publicationProceedings - 2021 International Seminar on Intelligent Technology and Its Application
Subtitle of host publicationIntelligent Systems for the New Normal Era, ISITIA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages391-395
Number of pages5
ISBN (Electronic)9781665428477
DOIs
Publication statusPublished - 21 Jul 2021
Event2021 International Seminar on Intelligent Technology and Its Application, ISITIA 2021 - Virtual, Online
Duration: 21 Jul 202122 Jul 2021

Publication series

NameProceedings - 2021 International Seminar on Intelligent Technology and Its Application: Intelligent Systems for the New Normal Era, ISITIA 2021

Conference

Conference2021 International Seminar on Intelligent Technology and Its Application, ISITIA 2021
CityVirtual, Online
Period21/07/2122/07/21

Keywords

  • clustering
  • liquid identification
  • optical instrumentation
  • principal component analysis
  • spectrophotometry

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