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Non-Enzymatic Detection of Glucose and Ketones in Urine using Paper-Based Analytical Devices 'Aisy, Kamila Rohadatul; Fahmi, Ahmad Luthfi; Sulistyarti, Hermin; Wulandari, Ika Oktavia; Sabarudin, Akhmad
JKPK (Jurnal Kimia dan Pendidikan Kimia) Vol 9, No 2 (2024): JKPK (Jurnal Kimia dan Pendidikan Kimia)
Publisher : Program Studi Pendidikan Kimia FKIP Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jkpk.v9i2.87294

Abstract

Diabetes, driven by unbalanced diets and unhealthy lifestyles, is highly prevalent. In Indonesia, its prevalence is projected to reach 28.6 million by 2045. Microfluidic paper-based analytical devices (μPADs) are paper-based analytical tools that use hydrophilic paper for measurement and hydrophobic barriers to control fluid flow. This research aims to develop a non-enzymatic method for detecting glucose and ketones in artificial urine using S2Z-μPADs. The fabrication of S2Z-μPADs involves printing the design on Whatman No. 1 paper using wax printing and applying silver nanoparticles for glucose detection and the Schiff base reaction for ketone detection. The results show that the optimum condition for glucose detection is achieved with an AgNO3 concentration of 500 mM. A NaOH concentration of 10 M. Acetoacetate detection is optimized with a glycine concentration of 1 M, sodium nitroprusside concentration of 15%, NaOH concentration of 1 M, a drying time of 8 minutes, and a reaction time of 10 minutes. Validation results demonstrate good linearity for glucose (R² = 0.9821) and ketones (R² = 0.995). High precision was achieved with relative standard deviation (RSD) values of 3.792% for glucose and 1.482% for ketones. The obtained limits of detection (LOD) and limits of quantification (LOQ) indicate that the developed S2Z-μPADs can differentiate between each category of diabetes. The accuracy of glucose and ketone detection ranges from 87.463% to 97.374%. The high accuracy of the μPADs highlights their potential for reliable diabetes management and effective disease monitoring.