• MUHAMAD SAHLAN Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Depok, West Java, 16424, Indonesia, Research Center for Biomedical Engineering, Faculty of Engineering, Universitas Indonesia, Depok, West Java, 16424, Indonesia
  • NUR ANNISA LUTHFIYAH AHLAM Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Depok, West Java, 16424, Indonesia
  • ALI AGUS Faculty of Animal Science, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia
  • ARDO SABIR Department of Conservative Dentistry, Faculty of Dentistry, Hasanuddin University, Makassar, South Sulawesi, 90245, Indonesia
  • DIAH KARTIKA PRATAMI Lab of Pharmacognosy and Phytochemistry, Faculty of Pharmacy, Pancasila University, Jakarta, 12640, Indonesia



Honey, ATR-FTIR, Raman, Discriminant analysis, Apis spp, Stingless bee


Objective: This study aims to develop a fast, fitted, and accurate classification method for authenticating honey.

Methods: The authentic honey samples were obtained from local beekeepers and distributors, while most of the adulterated honey samples were made from a mixture of fructose syrup, authentic honey, sodium bicarbonate, and sweet soy sauce, while others were received from local distributors. To authenticate the honey, samples were divided into two classes, real honey, and adulterated honey. Similarly, to classify the honey, we categorized two classes, Apis spp. and stingless bee. ATR-FTIR spectra data were collected using Thermo Scientific’s OMNIC FTIR software and processed using Thermo Scientific’s TQ Analyst software by dividing the wavelengths into six regions between 550-4000 cm-1. and Raman spectra data were collected using HORIBA LabSpec 6 software and processed using CAMO’s Unscrambler X10.4 software by dividing the Raman shifts into five regions between 200-3350 cm-1.

Results: Our methods effectively authenticate the honey-based on ATR-FTIR and Raman spectra. Based on ATR-FTIR spectra data, the best region of honey’s authenticity is Region 1,3,4,5,6 (2800-3000 cm-1; 1640-1760 cm-1; 1175-1455 cm-1; 950-1175 cm-1; 750-950 cm-1) and the best region for classification is 750-950 cm-1. Based on Raman spectra data, the best region of honey’s authenticity is 970-1150 cm-1 and the best region for classification are 1150-1480 cm-1 and 970-1480 cm-1.

Conclusion: This study successfully demonstrated accurate methods based on ATR-FTIR and Raman spectral data to authenticate and classify the honey.


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