Autentikasi Kumis Kucing (Orthosiphon Aristatus) Menggunakan Kombinasi Spektrum Ultraviolet-Tampak Dan Partial Least Square Regression

  • Mohamad Rafi Institut Pertanian Bogor
  • Nurul Sakinah W IPB University
  • Wulan Tri Wahyuni IPB University
  • Zulhan Arif IPB University
  • Rudi Heryanto IPB University
DOI: https://doi.org/10.22146/ijcpa.890
Keywords: Babadotan, Kumis Kucing, Tekelan, Kemometrik, Autentikasi, spektrum UV-vis

Abstract

Kumis kucing (Orthosiphon aristatus) merupakan salah satu tanaman obat yang banyak digunakan dalam mencegah maupun mengobati berbagai penyakit seperti memperlancar pengeluaran air kemih (diuretik), mengobati rematik, batuk, encok, masuk angin, sembelit, batu ginjal, kencing manis, dan albuminuria. Daun kumis kucing memiliki kemiripan dengan daun tekelan dan babadotan dalam bentuk daunnya, sehingga kedua daun tersebut dapat menjadi bahan pemalsu daun kumis kucing. Penelitian ini bertujuan mengembangkan metode analisis untuk mengidentifikasi dan mengautentikasi kumis kucing dari babadotan dan tekelan. Kombinasi spektrum ultraviolet-tampak dan partial least square regression digunakan dalam pengembangan metode tersebut. Kisaran panjang gelombang yang digunakan untuk identifkasi dan autentikasi adalah 210-500 nm. Prapemrosesan sinyal untuk data matriks spektrum ultraviolet-tampak dilakukan dengan transformasi detrending karena menghasilkan galat yang lebih kecil dibandingkan dengan proses transformasi lainnya. Hasil yang didapat menunjukkan nilai koefisien determinasi di atas 0.9 untuk kalibrasi dan validasi. Nilai root mean square error calibration yang sudah cukup rendah dan nilai root mean square error prediction yang tidak terlalu tinggi menunjukkan bahwa model yang dikembangkan masih cukup baik dalam menentukan adanya bahan pemalsu dalam sampel kumis kucing.

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Published
2021-07-29
How to Cite
Rafi, M., Sakinah W, N., Wahyuni, W. T., Arif, Z., & Heryanto, R. (2021). Autentikasi Kumis Kucing (Orthosiphon Aristatus) Menggunakan Kombinasi Spektrum Ultraviolet-Tampak Dan Partial Least Square Regression. Indonesian Journal of Chemometrics and Pharmaceutical Analysis, 1(2), 93-101. https://doi.org/10.22146/ijcpa.890
Issue
Vol 1 No 2 (2021)
Section
Original Articles

Copyright (c) 2021 Indonesian Journal of Chemometrics and Pharmaceutical Analysis

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