PENERAPAN ALGORITMA DISKRIMINASI MENGGUNAKAN METODE PRINCIPAL COMPONENT ANALYSIS (PCA) DAN Vis-SWNIR SPECTROSCOPY PADA BUAH CABAI RAWIT DOMBA BERBAGAI TINGKAT KEMATANGAN

Authors

  • Ine Elisa Putri Universitas Padjadjaran
  • Kusumiyati Kusumiyati Universitas Padjadjaran
  • Agus Arip Munawar Universitas Syiah Kuala

Keywords:

Classification, Hotelling’s T2, NIPALS, prediction

Abstract

Cayenne pepper fruit can be used for health because it is a source of antioxidants. Detection of quality fruit can use non-destructive methods as an alternative method. Visible short wavelength near infrared (Vis-SWNIR) spectroscopy is non-destructive measurement. This method can be used to discriminate fruit by using the principal component analysis (PCA). This research aimed to discriminate between Cayenne pepper with various maturity by using Vis-SWNIR spectroscopy with a wavelength of 300-1065 nm and principal component analysis (PCA). Cayenne pepper fruit was devided into three groups, namely green, orange and red. The spectrum used the absorbance spectrum data (original). The research was carried out from March to June 2020. The result showed that the use of Vis-SWNIR and PCA were able to discriminate various maturity of cayenne pepper with a 100% success rate.

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Published

2021-04-21

How to Cite

[1]
I. E. . Putri, K. Kusumiyati, and A. A. . Munawar, “PENERAPAN ALGORITMA DISKRIMINASI MENGGUNAKAN METODE PRINCIPAL COMPONENT ANALYSIS (PCA) DAN Vis-SWNIR SPECTROSCOPY PADA BUAH CABAI RAWIT DOMBA BERBAGAI TINGKAT KEMATANGAN ”, SINTECH Journal, vol. 4, no. 1, pp. 40-46, Apr. 2021.