Article Per Year (5 Year)
p-Index From 2020 - 2025
0.562
P-Index
This Author published in this journals
All Journal Food and Agro-industry (FAGI) Journal Food and Agro-industry (FAGI) Journal The Indonesian Journal of Computer Science
Suwati
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
KAJIAN RASIO BUBUR SALAK (Salacca edulis) DENGAN BUBUR WORTEL (Daucus carota L.) TERHADAP SIFAT KIMIA DAN ORGANOLEPTIK SIRUP SALAK Muhammad Faisal; Suwati; Syirril Ihromi; Hutasoit Hutasoit
The Journal of Teknologi Pangan Vol 3 No 2 (2022): Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering
Publisher : Faculty of Agricultural Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Buah salak merupakan buah tropis yang tersebar di Asia tenggara secara khusus Indonesia, yang dapat digunakan sebagai bahan pembuatan minuman. Kombinasi dengan bahan lain untuk memperkaya kandungan gizi sirup yang dihasilkan seperti penambahan dengan buah wortel diperlukan. Tujuan dari penelitian ini adalah mengetahui pengaruh kombinasi penambahan bubur salak, wortel dan gula terhadap kadar gula reduksi, kadar beta karoten dan sifat organoleptik sirup salak. Penelitian ini menggunakan RAL (Rancangan Acak Lengkap) dengan perlakuan dua faktor yaitu faktor  I terdiri dari 4 level yaitu : W1 = Tanpa perbandingan bubur wortel (100 % bubur salak), W2 = 90 % Bubur salak + 10 % bubur wortel, W3 = 80 % Bubur salak + 20 % bubur wortel dan W4 = 70 % Bubur salak + 30 % bubur wortel. Sedangkan faktor II terdiri dari 2 level yaitu : G1 = kosentrasi gula 25 % dan G2 = Kosentrasi gula 50%. Sehingga didapatkan 8 kombinasi perlakuan. Masing-masing perakuan diulang sebanyak 2 kali sehingga didapatkan 16 unit percobaan. Analisis parameter yang dilakukan meliputi kadar gula reduksi, kadar betakaroten, warna, aroma dan rasa. Data pengamatan dianalisis menggunakan analisis sidik ragam pada taraf nyata 5 % dan diuji lanjut dengan menggunakan uji Beda Nyata Jujur (BNJ) pada tingkat yang sama. Hasil penelitian menunjukkan bahwa perlakuan kombinasi penambahan bubur salak dan wortel dengan konsentrasi gula berpegaruh nyata terhadap warna dan aroma sirup salak, sedangkan kadar gula reduksi, kadar beta karoten dan uji rasanya berpengaruh tidak nyata. Perlakuan W2G2 (450 gr bubur salak + 50 gr bubur wortel) dan konsentrasi gula 50% memberikan hasil yang terbaik pada uji organoleptik sirup salak
KAJIAN RASIO BUBUR SALAK (Salacca edulis) DENGAN BUBUR WORTEL (Daucus carota L.) TERHADAP SIFAT KIMIA DAN ORGANOLEPTIK SIRUP SALAK Muhammad Faisal; Suwati; Syirril Ihromi; Hutasoit Hutasoit
The Journal of Teknologi Pangan Vol 3 No 2 (2022): Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering
Publisher : Faculty of Agriculture Science & Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Snake fruit is a tropical fruit that is spread throughout Southeast Asia, specifically Indonesia, and can be used as an ingredient in drinks. In making syrup, the raw materials used usually consist of only one type of fresh fruit, so it is necessary to combine it with other ingredients to improve the nutritional content of the resulting syrup, such as adding carrots. The purpose of this study was to determine the effect of adding snake fruit puree, carrots, and sugar on reducing sugar levels, beta-carotene levels, and the organoleptic properties of snake fruit syrup. This study used a CRD (completely randomized design) with treatment of two factors, namely factor I, consisting of four levels: W1 = without comparison of carrot pulp (100% snake fruit puree), W2 = 90% snake fruit puree + 10% carrot puree, W3 = 80% snake fruit puree + 20% carrot puree, and W4 = 70% snake fruit puree + 30% carrot puree. While factor II consisted of 2 levels, namely, G1 = 25% sugar concentration and G2 = 50% sugar concentration, in order to obtain eight treatment combinations Each treatment was repeated twice to obtain 16 experimental units. Parameter analysis carried out included reducing sugar levels, beta-carotene levels, color, aroma, and taste. Observational data were analyzed using analysis of variance at a significant level of 5%. If the treatment is significantly different, then it will be further tested using the Honest Significant Difference (HSD) test at the same level. Combining snake fruit puree and carrots with sugar concentration had a significant effect on the color and aroma of snake fruit syrup, but lowering sugar levels, beta-carotene levels, and taste tests had no effect. The W2G2 treatment (450 g of snake fruit puree and 50 g of carrot puree) and 50% sugar concentration gave the best results in the organoleptic test of snake fruit syrup.
Prediksi Kelancaran Pembayaran Angsuran Pada Koperasi Dengan Metode Naive Bayes Classifier Suwati; Yesputra, Rolly; Sapta, Andy
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3080

Abstract

This study aims to predict the smoothness of installment  payments in cooperatives, making it easier for staff to analyze credit lending. Lack of prudence in analyzing credit results in customers who are in arrears in paying installments, resulting in bad credit. To minimize errors that exist, it is necessary to evaluate the provision of loans to prospective debtors. By utilizing past member criteria data in the past that will be used to predict smooth payments using data mining. The data mining technique used is the Naive Bayes classifier method. The prediction process uses the naive Bayes method, namely by determining the probability or opportunity based on the previous member's data, and the results are used to help make a decision. The criteria used are member data: employment, income, house status, number of credits, and type of credit. Based on the naive Bayes method, the results obtained are 90.00% accuracy, 0.880% AUC, 83,33% recall, and 100% precision.
Co-Authors Hutasoit Hutasoit Muhammad Faisal Muhammad Faisal Rolly Yesputra Sapta, Andy Syirril Ihromi, Syirril