Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Engineering and Management in Industrial System Jurnal Teknologi Informasi dan Ilmu Komputer
Danang Triagus Setiyawan
Unknown Affiliation
Computer Science & IT Engineering Industrial & Manufacturing Engineering

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

Found 2 Documents
Search

 1 
Deteksi Cepat Kadar Alkohol Pada Minuman Kopi dengan Metode Dielektrik dan Jaringan Syaraf Tiruan Sucipto, Sucipto; Rohmawati, Yuyun; Widyaningrum, Dyah Ayu; Setiyawan, Danang Triagus
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 1: Februari 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022913588

Abstract

Penambahan whiskey pada minuman kopi menjadi problem bagi konsumen. Pengukuran perbedaan nilai sifat biolistrik setiap bahan diharapkan dapat memprediksi kadar alkohol dalam minuman kopi. Tujuan penelitian ini adalah untuk memprediksi kadar alkohol dan pH minuman kopi berbasis sifat biolistrik bahan dan Jaringan Syaraf Tiruan (JST). Algoritma backpropagation digunakan menghubungkan input sifat biolistrik dan output prediksi kadar alkohol dan pH minuman kopi ditambah whiskey. Hasil penelitian menunjukkan minuman kopi bersifat kapasitif bahkan resistif. Analisis sensitivitas dengan input sifat biolistrik (induktansi, kapasitansi, resistansi dan impedansi) dan output kadar alkohol dan pH didapat topologi JST terbaik yaitu 4-10-30-2. Pada topologi JST terbaik didapat MSE pelatihan 0,000948 dan MSE validasi 0,0011 serta koefisien korelasi (R) pelatihan sebesar 0,99929 dan R validasi 0,99985. Hasil ini membuka peluang pengembangan teknik deteksi cepat kadar alkohol dalam minuman kopi berbasis sifat biolistrik dengan pemodelan JST. AbstractWhiskey addition in the coffee drinks is a problem for consumers. Measurement of differences in the value of the bioelectric properties of each ingredient is expected to predict alcohol content in coffee drinks. The purpose of this study was to estimate the alcohol content and pH of coffee drinks based on the bioelectric of material and Artificial Neural Networks (ANN). The back propagation algorithm was used to connect the input of bioelectric properties and output of prediction of alcohol content and pH in liqueur coffee. The results showed that liqueur coffee are capacitive and even resistive. Sensitivity analysis with bioelectric properties as input (inductance, capacitance, resistance, and impedance) and alcohol and also pH as output obtained the best ANN topology, 4-10-30-2. The best ANN topology had Mean Standard Error (MSE) of training of 0.000948 and validation MSE of 0.0011 with the correlation coefficient (R) of training and validation of 0.99929 and 0.99985, respectively. These results open up opportunities for the development of rapid alcohol content detection techniques based on bioelectric properties with ANN models for coffee drinks.
MINIMASI WASTE UNTUK PERBAIKAN PROSES PRODUKSI KANTONG KEMASAN DENGAN PENDEKATAN LEAN MANUFACTURING Setiyawan, Danang Triagus; Soeparman, Sudjito; Soenoko, Rudy
JEMIS (Journal of Engineering & Management in Industrial System) Vol. 1 No. 1 (2013)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jemis.2013.001.01.2

Abstract

Packaging Factory have activities in  bag production. In order to increase the productivity, the company should manage the activities to increase valued added and decrease several waste. This study was purpose for analyzed the caused problems of waste, and give recommendation for minimizing the waste.  The problem solving at the study was using lean manufacturing concept approach.  The waste identification began with identification of  current state value stream mapping with weighting the waste in order to  understand the root of problem within production process.  The detail mapping selection was using Value Stream Analysis Tools (VALSAT).  Root Cause Analysis was used in order to understanding the root of problem for production process followed by FMEA for understanding the improving priority which has to be done. From the data analysis result, we found that the most dominant waste order is defect, waiting,  inventory, excessive transportation.The mapping detail used for analysis process as Process Activity Mapping Supply Chain Response Matrix and Quality Filter Mapping. From the result of study we found the decreasing of production time from 138.4 minute to 119.4 minute.  Decreasing lead time process could reach 13,7% comparing before the recovery step. 
Co-Authors Rohmawati, Yuyun Rudy Soenoko Sucipto Sucipto Sudjito Soeparman Widyaningrum, Dyah Ayu