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All Journal Chemistry Indonesian Journal of Chemical Research
Mamluatul Faizah
Department of Medical Laboratory Technology, STIKES Banyuwangi, Jl. Letkol Istiqlah No. 109 Banyuwangi
Biochemistry, Genetics & Molecular Biology Chemistry Engineering Environmental Science

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Development of a Rapid Paper Test Kit Method Based on Silver Nanoparticles for Early Detection of Stroke Disease Hanim Istatik Badi'ah; Mamluatul Faizah
Indonesian Journal of Chemical Research Vol 13 No 3 (2026): Edition for January 2026
Publisher : Jurusan Kimia, Fakultas Sains dan Teknologi, Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/ijcr.2026.13-han

Abstract

Stroke is one of the leading causes of death worldwide, there’s a need for rapid and affordable diagnostic tools. This study developed a paper test kit based on a colorimetric sensor utilizing silver nanoparticles (AgNp) synthesized via sodium borohydride (NaBH4) reduction for cortisol detection as a biomarker related to stroke disease. The synthesized AgNp showed a distinct surface plasmon resonance peak at around 402 nm by UV-Vis spectrophotometry, confirming successful nanoparticle formation. Particle size analyzer (PSA) revealed uniform nanoscale distribution, with an average particle size of approximately 25 – 40 nm. The immobilization techniques of layer by layer and immersion were compared for embedding AgNp onto the paper substrate. The LBL technique is more suitable for analytical precision and reproducibility, while the immersion technique is advantageous for rapid, large-area production of paper-based colorimetric sensors. The developed paper taper testing kit exhibited a gradual color change from yellow to brown with increasing cortisol concentration. The quantitative value as a linear correlation and sensitivity was 0.09984 and 0.069 µM/mL, respectively. The RGB value of the developed paper test kit is (210, 180, 140). The results highlight the potential of the AgNp-based paper sensor as rapid and portable analytical platform for cortisol detection.
Co-Authors Hanim Istatik Badi'ah