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All Journal Jurnal Penelitian Saintek SINTECH (Science and Information Technology) Journal
Ine Elisa Putri
Universitas Padjadjaran
Computer Science & IT Decision Sciences, Operations Research & Management

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Aplikasi VIS/NIR spectroscopy dan partial least square regression untuk pendugaan nilai warna kulit buah cabai rawit Kusumiyati Kusumiyati; Ine Elisa Putri; Wawan Sutari; Jajang Sauman Hamdani
Jurnal Penelitian Saintek Vol 27, No 1 (2022)
Publisher : Institute of Research and Community Services, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jps.v1i1.47930

Abstract

Warna kulit buah buah cabai rawit (Capsicum Frutescens L.) merupakan salah satu indikator dari kematangan buah. Visible/near infrared (Vis/NIR) spectroscopy merupakan teknologi alternatif untuk memprediksi warna kulit buah yang dikombinasikan dengan partial least square regression (PLSR). Penelitian ini bertujuan untuk memprediksi warna kulit buah cabai rawit menggunakan Vis/NIR spectroscopy. Analisis di Laboratorium Hortikultura, Fakultas Pertanian, Universitas Padj+!adjaran. Sampel yang digunakan yaitu buah cabai rawit var. Domba. Sampel dibagi ke dalam 3 grup, buah cabai rawit hijau, oranye, dan merah. Spectrometer yang digunakan yaitu NirVana AG410 dengan panjang gelombang 300-1065 nm dengan interval 3 nm. Semua data absorban dikoreksi dengan menggunakan metode prapengolahan spektra multiplicative scatter correction (MSC), orthogonal signal correction (OSC), dan standard normal variate (SNV). Hasil penelitian menunjukkan bahwa prapengolahan spektra terbaik untuk memprediksi L*dan b* pada buah cabai rawit yaitu PLSR+OSC sedangkan a* yaitu PLSR+SNV. Nilai akurasi L* dengan OSC yaitu R kalibrasi = 0,99 dan b* dengan OSC yaitu R kalibrasi = 0,76. Akurasi pada a* dengan SNV menghasilkan R kalibrasi = 0.99. Penelitian ini membuktikan bahwa Vis/NIR spectroscopy dan PLSR memiliki akurasi yang tinggi dan dapat digunakan untuk memprediksi warna kulit buah cabai rawit.Application of VIS/NIR spectroscopy and partial least square regression for estimation of skin color in cayenne pepper fruitThe skin fruit color of cayenne pepper (Capsicum Frutescens L.) is one of indicators of fruit maturity. Visible/near infrared (Vis/NIR) spectroscopy is alternative technology to predict of skin color fruit combined with partial least square regression (PLSR). The research was aimed to predict skin color fruit of cayenne pepper using Vis/NIR spectroscopy. Analysis at Horticulture Laboratory, Faculty of Agriculture, Universitas Padjadjaran. The samples used was cayenne pepper var. Domba. The smples were divided into 3 groups, green, orange red cayenne pepper. The spectrometer used was NirVana AG410 spectrometer with 300 to 1065 nm with 3 nm intervals. All of absorbance data were pre-treated using spectra correction methods including multiplicative scatter correction (MSC), orthogonal signal correction (OSC) dan standard normal variate (SNV). The result showed that the best spectra correction method for predicting L*and b* in cayenne pepper was PLSR+ OSC while a*was PLSR+ SNV. The accuracy value of * with OSC is R calibration = 0.99 and b*with OSC is R calibration = 0.76. This research resumed that Vis/NIR spectroscopy and PLSR have high accuracy and can be used to predict the skin color of cayenne pepper fruit.
PENERAPAN ALGORITMA DISKRIMINASI MENGGUNAKAN METODE PRINCIPAL COMPONENT ANALYSIS (PCA) DAN Vis-SWNIR SPECTROSCOPY PADA BUAH CABAI RAWIT DOMBA BERBAGAI TINGKAT KEMATANGAN Ine Elisa Putri; Kusumiyati Kusumiyati; Agus Arip Munawar
SINTECH (Science and Information Technology) Journal Vol. 4 No. 1 (2021): SINTECH Journal Edition April 2021
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v4i1.680

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.
Co-Authors Agus Arip Munawar Jajang Sauman Hamdani Kusumiyati Wawan Sutari