Article Per Year (5 Year)
p-Index From 2019 - 2024
0.444
P-Index
This Author published in this journals
All Journal REACTOR : Journal of Research On Chemistry And Engineering Teknologi dan Industri Pertanian Indonesia
Murna Muzaifa
Program Studi Teknologi Hasil Pertanian Universitas Syiah Kuala
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Chemistry Energy Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Kajian Mutu Kimia Bubuk Kopi Espresso Aceh Berdasarkan Rasio Pencampuran Varietas Kopi Arabika dan Robusta dan Teknik Penyangraian Dian Hasni; Murna Muzaifa; Dedy Rahmad; Maulana Insan
REACTOR: Journal of Research on Chemistry and Engineering Vol 2, No 2 (2021): Published in December 2021
Publisher : Politeknik ATI Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52759/reactor.v2i2.31

Abstract

Generally there are two coffee varietes cultivated in Indonesia, known as Arabica and Robusta coffee. Arabica distinctively known for its distinctive quality but limited quantity compared to robusta which is commonly use for commercial coffee production due to its robust productivity. Nowadays, global market demand encourages a huge variety of coffee product, based on coffee such as espresso. The quality of espresso is influence by many factors such as roasting technique and ratio blending of coffee ground. This study aims to determine the influence of blending ratio and roasting techniqus to the chemical compounds of coffee ground and its espresso brewed. This research used Factorial Random Design, consists of 2 factors. First factor is ratio of blending Arabica and Robusta with three levels ratio; B1=70:30; B2=80:20; and B3=90:10). The second factor is roasting technique, consisting of 2 levels of conventional roasting(P1) and torrefacto (P2). Each treatment was repeated 3 replications to obtain 18 units of experiment. Measured parameters are pH of brewed espresso and moisture (%), ash (%), protein (%), lipid (%) and caffeine (%) contents of coffee ground. The results showed that the blending ratio was highly significant (P≤0,01) to the moisture and protein contents of coffee grounds and pH of resulted espresso. The best treatment was obtained from combination of B1P1 treatment (combination blending ratio (70%:30%) and conventional roasting) with 2.00% moisture content, 4.83% ash, 13.04% protein, 10.41% fat, 81.17% carbohydrate and caffeine 1.49%.
Apilikasi Matematika Linear Dalam Penyusunan Formulasi Optimum Pencampuran Kopi Arabika Gayo (Coffeea Arabica. L) Dian Hasni; Muhammad Nazawi; Heru Prono Widayat; Murna Muzaifa; Yusya' Abubakar
Jurnal Teknologi dan Industri Pertanian Indonesia Vol 15, No 1 (2023): Vol. (15) No. 1, April 2023
Publisher : Agricultural Faculty

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (624.892 KB) | DOI: 10.17969/jtipi.v15i1.24095

Abstract

Coffee is an Indonesian commodity that has a high selling price. Gayo Highland is known for arabica coffee plantation site in Aceh, where commonly three local cultivars are cultivated. These are Timtim or Gayo 1, Borbor or Gayo 2 and Ateng Super. All three cultivars complied as specialty coffee with cuptest score 84,50 (Timtim), 85.25 (Borbor) and 85.50 (Ateng Super) and each cultivar has distinctive aroma and flavour. Blending is one common practice before coffee brewing in order to optimize the cupping quality of coffee. This study aims to optimize the total cup test of blended coffee from three local cultivars of arabica coffee over 85 by using simple linear mathematics models. The hypotheses was a predicted cuptest score is equivalent with the laboratory cuptest score. Based on previous research, seven formulations were set up by using three local cultivars. Then two linear models were created based on specific constraints such as attribute score and cultivar ratio. The seven formulations are calculated in two assigned linear models as two replications. First model produced predicted score in between 84,15-85,38 and mean 84,88 whilst second model has a score range 84,07-85,13 with mean 84,80.  From all seven formulation, in these two linear models R3 and R7 has predicted cuptest score over 85. By using t-test, there is not significant difference available within the laboratory score and predicted score. It can be said the hypotheses is accepted and these two linear models could be used separately and or intentionally to predict cuptest score of blended coffee before blending is performed.
Co-Authors Dedy Rahmad Dian Hasni, Dian Heru Prono Widayat Maulana Insan Muhammad Nazawi Yusya' Abubakar