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All Journal Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering)
Cicih Sugianti
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 UNTUK IDENTIFIKASI CAMPURAN KOPI LUWAK DENGAN KOPI ARABIKA Cicih Sugianti; Novi Apratiwi; Diding Suhandy; Mareli Telaumbanua; Sri Waluyo; Meinilwita Yulia
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 5, No 3 (2016)
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1001.667 KB) | DOI: 10.23960/jtep-l.v5i3.%p

Abstract

This study aims to identify the authentication of civet coffee using a Soft independent modeling of class analogy(SIMCA) method and principal component analysis (PCA). The test carried out on the coffee powder measuring0.297 millimeters (mesh 50). Comparison of blend that is samples 1- 50 each 1 g of pure civet coffee, samples51- 60 each 0.9 g civet coffee and 0.1 g arabica coffee, samples 61-70 each 0.8 g civet coffee and 0.2 g arabicacoffee, samples 71-80 each 0.7 g civet coffee and 0.3 g arabica coffee, samples 81-90 each 0.6 g civet coffee and0.4 g arabica coffee, samples 90-100 each 0.5 g civet coffee and 0.5 g arabica coffee. The classification resultsshow SIMCA and PCA methods are able to identify civet coffee mixture. PC 1 explains 75% the variance of dataand PC2 explains 17% the variance of data. Values obtained on SIMCA classification are specificity 76%,sensitivity of 84% and accuracy of 80%, with a value error of 23%.Keywords: Arabica coffee,civet coffee, PCA, SIMCA, UV-Vis spectroscopy.
Co-Authors Diding Suhandy Fipit Novi Handayani Mareli Telaumbanua Meinilwita Yulia Meinilwita Yulia Novi Apratiwi Sri Waluyo Winda Rahmawati