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All Journal Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering)
Meinilwita Yulia
Department of Agricultural and Biological Engineering
Agriculture, Biological Sciences & Forestry Engineering

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ANALISIS SPEKTRUM UV-VIS UNTUK MENGUJI KEMURNIAN KOPI LUWAK Sri Waluyo; Fipit Novi Handayani; Diding Suhandy; Winda Rahmawati; Cicih Sugianti; Meinilwita Yulia
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 6, No 2 (2017)
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (262.034 KB)

Abstract

Penelitian ini bertujuan untuk membangun dan menguji model untuk identifikasi kemurnian kopi asli Luwak. Bahan yang digunakan adalah 100% kopi Luwak dan kopi Luwak yang dicampur dengan kopi Robusta dengan perbandingan pencampuran 90%: 10%, 80%: 20%, 70%: 30%, 60%: 40%, dan 50%: 50%. Pada penelitian ini model dibangun dan diprediksi menggunakan metode soft independent modeling of class analogy (SIMCA) dengan taraf signifikan10%, kemudian menghitung tingkat akurasi (AC), sensitivitas (S), spesifisitas (SP), dan false alarm rate (FP) menggunakan perhitungan confusion matrix. Dari proses Hotelling T2 elipse 95 sampel, diperoleh dua model untuk mengelompokkan kopi Luwak asli (SLWK) dan kopi campuran Luwak Robusta (SLWKR). Dari uji model didapat nilai akurasi (AC) 48,48%, sensitivitas (S) 50,00%, spesifisitas (SP) 33,33%, dan false alarm rate (FP) 66,67%.Kata Kunci : Kopi Luwak; Robusta; UV-vis spectroscopy; Pemodelan; Validasi
STUDI PENGGUNAAN UV-VIS SPECTROSCOPY DAN KEMOMETRIKA UNTUK MENGIDENTIFIKASI PEMALSUAN KOPI ARABIKA DAN ROBUSTA SECARA CEPAT Meinilwita Yulia; Riri Iriani; Diding Suhandy; Sri Waluyo; Cicih Sugianti
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 6, No 1 (2017)
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (331.022 KB) | DOI: 10.23960/jtep-l.v6i1.%p

Abstract

There are two popular coffees in Indonesia, namely Arabica and Robusta coffees. Arabica coffee has a better quality than Robusta do. This research aimed to identify the  purity of Arabica coffee; and Robusta as mixture ingredient, by using technology of UV-Vis spectroscopy and multivariate analysis, with a method of soft independent modelling of class analogy (SIMCA) and principal component analysis (PCA). The research was conducted using coffee powder with size 0,297 millimeters (50 mesh).The research used 100 samples; sample 1-50 (1 g of Arabica), sample 51-60  (0,8 g of Arabica and 0,2 of Robusta), sample 61-70 (0,7 g of Arabica and 0,3 g of Robusta), sample 71-80 (0,6 g of Arabica and 0,4 of Robusta) sample 81-90 (0,5 g of Arabica and 0,5 g of Robusta), sample 91-100 (0,4 g of Arabica and 0,6 g of Robusta).  The result of classification showed that method of PCA and SIMCA are able to classify the mixture of pure Arabica. PC1 explained 77% various datas, and PC2 explained 10% various datas, whilst from data classification SIMCA obtained the precentage score onaccuracy 56%, sensitivitas 58%, and spesifisitas 0%.Keywords: Arabica coffee, Robusta coffee, PCA, SIMCA, UV-Vis spectroscopy
Co-Authors Cicih Sugianti Diding Suhandy Fipit Novi Handayani Riri Iriani Sri Waluyo Winda Rahmawati