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    Model Kalibrasi Kandungan Kafein pada Kopi Green Bean Arabika Mandailing Natal Menggunakan Nirs dan Jaringan Saraf Tiruan

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    Date
    2021
    Author
    Hrp, Jumadil Akhir
    Advisor(s)
    Panggabean, Sulastri
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    Abstract
    Generally, Near Infrared Reflectance (NIR) spectroscopy is a nondestructive method that can identify the chemical content of agricultural products including Mandailing Natal Arabica coffee. This study aims to obtain the NIR spectra of Mandailing Natal arabica coffee and a calibration model of caffeine content using (ANN). The NIRS data pretreatment used were segmentation, normalization and MSC. The results of this study found the caffeine content of Mandailing Natal green bean arabica coffee at wavelengths of 1,208.9 nm and 1,728.91 nm. The best ANN architecture is 10-3-1 at 10,000 iterations with segmentation of 6 and data normalization. This architecture is evaluated with the values of r, R2, CV and │RMSEC-RMSEP│ which are obtained of 0.9131, 0.8338, 6.2% and 0.04145, respectively. Whereas for the MSC segmentation 8 pretreatment, the best network architecture is 13-3-1 at 1,000 iterations. Obtained the value of r = 0.9845, R2 = 0.9692, cv = 4.80% and RMSEC-RMSEP│ which is 0.0383.
     
    Umumnya spektroskopi Near Infrared Reflectance (NIR) merupakan metode nondestruktif yang dapat mengidentifikasi kandungan kimia produk pertanian termasuk kopi arabika Mandailing Natal. Penelitian ini bertujuan untuk mendapatkan spektra NIR kopi arabika Mandailing Natal dan model kalibrasi kandungan kafein menggunakan (JST). Pretreatment data NIRS yang digunakan adalah segmentasi, normalisasi dan MSC. Hasil dari peneltian ini ditemukan kandungan kafein kopi arabika green bean Mandailing Natal pada panjang gelombang 1.208,9 nm dan 1.728,91 nm. Arsitektur JST terbaik adalah 10-3-1 pada iterasi 10.000 dengan segmentasi 6 dan normalisasi data. arsitektur ini dievaluasi dengan nilai r, R2, CV dan │RMSEC-RMSEP│yang diperoleh masingmasing sebesar 0,9131, 0,8338, 6,2% dan 0,04145. Sedangkan untuk pretreatment MSC segmentasi 8, arsitektur jaringan terbaik adalah 13-3-1 pada iterasi 1.000. diperoleh nilai nilai r = 0,9845, R2 = 0,9692, cv = 4,80% dan│RMSECRMSEP │yaitu sebesar 0,0383.

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    https://repositori.usu.ac.id/handle/123456789/44515
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    • Undergraduate Theses [1076]

    Repositori Institusi Universitas Sumatera Utara - 2025

    Universitas Sumatera Utara

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    Repositori Institusi Universitas Sumatera Utara - 2025

    Universitas Sumatera Utara

    Perpustakaan

    Resource Guide

    Katalog Perpustakaan

    Journal Elektronik Berlangganan

    Buku Elektronik Berlangganan

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV