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Hapsoro Agung Jatmiko
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Universitas Ahmad Dahlan, 4th Campus Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191 Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604
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International Journal of Industrial Optimization (IJIO)
Published by Universitas Ahmad Dahlan
ISSN : 27146006     EISSN : 27233022     DOI : https://doi.org/10.12928/ijio.v1i1.764
Core Subject : Science, Engineering,
Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering
The Journal invites original articles and not simultaneously submitted to another journal or conference. The whole spectrums of Industrial Engineering are welcome but are not limited to Metaheuristics, Simulation, Design of Experiment, Data Mining, and Production System. 1. Metaheuristics: Artificial Intelligence, Genetic Algorithm, Particle Swarm Optimization, etc. 2. Simulations: Markov Chains, Queueing Theory, Discrete Event Simulation, Simulation Optimization, etc. 3. Design of experiment: Taguchi Methods, Six Sigma, etc. 4. Data Mining: Clustering, Classification, etc. 5. Production Systems: Plant Layout, Production Planning, and Inventory Control, Scheduling, System Modelling, Just in Time, etc.
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 6 Documents
 1 
Search results for , issue "Vol. 1 No. 2 (2020)" : 6 Documents clear
The optimization of distribution and transportation costs for common good products Fibi Eko Putra; Humiras Hardi Purba; Indah Astri Anggraeni
International Journal of Industrial Optimization Vol. 1 No. 2 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i2.2368

Abstract

Transportation problems, which concerned in finding the minimum cost of transporting a single commodity from a given number of sources to a given number of destinations, are an integral part of the industrial system that has been around for a long time. The number of potential losses caused by transportation problems has made many parties take initiatives and efforts to solve those problems, usually by designing an optimal distribution model. The current study employs two methods named North West Corner (NWC) and Stepping Stone (SS) method in order to find distribution model with the most optimal costs for common good products. Through this research, the NWC method is utilized to generate initial model or solution, while the SS method is used afterward to find the optimal solution. According to it scheme, the result shows that through the NWC method there was cost reduction of $ 8,301, while the distribution model obtained from the Stepping Stone method resulted in a significant cost increased of $ 307,369. Thus, it can be concluded that the use of single method, namely NWC method, in this study provides much better results than using the combined NWC and Stepping Stone method.
Application of taguchi experiment design to reduce lignin contents of rice straw Selvia Aprilyanti; Faizah Suryani; Azhari Azhari
International Journal of Industrial Optimization Vol. 1 No. 2 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i2.2400

Abstract

The Taguchi experimental design is an experimental design to get the quality of an object by providing the best design at the procurement stage. In this case, the Taguchi design was applied to reduce the contents of lignin from rice straw, where lignin is one of the rice straw components that useless which must be reduced or eliminated. Rice straw is composed of lignin, cellulose, and hemicellulose. The existence of lignin components that become a protective wall will inhibit the activity of cellulose, and hemicellulose for further processing to produce some fermented products such as bio-gas, bio-ethanol, bio-plastics, and others. The process of decreasing lignin content from rice straw is done in ozonolysis. In this study, Taguchi's experimental design analysis was using the application of MINITAB 14 which used for statistical calculation and create a level setting in a tabular form of arrays called orthogonal arrays. The orthogonal array matrix used is L9 (33 ) which states that the process was conducted 9 times with variations of 3 factors and 3 levels. The factors that influence the decrease in lignin levels include sample size, ozone flow rate, and contact time. The results showed that the smallest lignin content was carried out at 80 mesh sample size, the ozone flow rate of 3 L / Min, and contact time for 10 minutes.
Queue analysis of public healthcare system to reduce waiting time using flexsim 6.0 Putri Amalia; Nur Cahyati
International Journal of Industrial Optimization Vol. 1 No. 2 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i2.2428

Abstract

Public healthcare is a health service facility from the government at a low cost. The problem is the long queue, which makes long patients’ waiting times. The patients are waiting for a maximum of more than 3 hours in the general polyclinic. Besides, the registration counter is almost busy all the time. The utilization is about 96.96%. Therefore, the objective of this research is to reduce the patients’ waiting time using the simulation method. Flexsim 6.0 software is employed to develop the public healthcare system and also develop some alternatives to improve the problem. The simulation model has been verified and validated. The result shows the waiting time is decreased by more than 80% by adding the resource in the registration counter. For managerial insight, this research could help the public healthcare system in satisfying the patients.
Quality by design of yogurt product using taguchi multi responses method Ali Parkhan; Muhammad Ridwan Andi Purnomo
International Journal of Industrial Optimization Vol. 1 No. 2 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i2.2442

Abstract

Quality of yogurt could be determined based on its flavor and texture which could be tested using an organoleptic test. The quality objective of the yogurt flavor and texture is larger the better. As one of the intermediate products that could be processed to become various other products, the demand for yogurt is continuously increasing in Indonesia. Along with the increase in demand, the demand for quality of yogurt has also increased. In this study, experiments have been conducted to improve the quality of a yogurt product. The experiments were designed based on the Taguchi method with Multi Responses Signal to Noise (MRSN) that involves 7 factors consists of 6 controllable factors and 1 uncontrollable factor. Every factor has 2 levels of an experiment. The 6 controllable factors are heating temperature, heating duration, number of yogurt seeds, incubation temperature, incubation duration, number of sugars, while the uncontrollable factor is the weather condition. Result of the experiments showed when weight for flavor and texture is 0.437 and 0.563 respectively, the levels of the optimum factors are 950C for milk heating temperature, 20 minutes for the duration of milk heating process, 75 ml of yogurt seeds, 450C of the temperature of incubation, 6 hours of incubation duration and 12.5 grams of sugar weight. Based on the organoleptic test that conducted by a group of experienced testers, the new optimum factors combination could improve the yogurt’s quality in term of flavor and quality up to 16.24% and 11.37% respectively. It could be concluded that the proposed method could improve the quality of yogurt-based on preferences from the experienced testers that have been expressed by the weight of every quality response.
Gas lift optimization in the oil and gas production process: a review of production challenges and optimization strategies Ikenna Tobechukwu Okorocha; Chuka Emmanuel Chinwuko; Chika Edith Mgbemena; Chinedum Ogonna Mgbemena
International Journal of Industrial Optimization Vol. 1 No. 2 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i2.2470

Abstract

Gas Lift operation involves the injection of compressed gas into a low producing or non-performing well to maximize oil production. The oil produced from a gas lift well is a function of the gas injection rate. The optimal gas injection rate is achieved by optimization. However, the gas lift, which is an artificial lift process, has some drawbacks such as the deterioration of the oil well, incorrect production metering, instability of the gas compressor, and over injection of gas. This paper discusses the various optimization techniques for the gas lift in the Oil and Gas production process. A systematic literature search was conducted on four databases, namely Google Scholar, Scopus, IEE Explore and DOAJ, to identify papers that focused on Gas lift optimizations. The materials for this review were collected primarily via database searches. The major challenges associated with gas lift were identified, and the different optimization strategies available in the literature reviewed. The strategies reviewed were found to be based on artificial intelligence (AI) and machine learning (ML). The implementation of any of the optimization strategies for the gas lift will enhance profitability, reduce operational cost, and extend the life of the wells.
Currency movement forecasting using time series analysis and long short-term memory Kristina Sanjaya Putri; Siana Halim
International Journal of Industrial Optimization Vol. 1 No. 2 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i2.2490

Abstract

Foreign exchange is one type of investment, which its goal is to minimize losses that could occur. Forecasting is a technique to minimize losses when investing. The purpose of this study is to make foreign exchange predictions using a time series analysis called Auto-Regressive Integrated Moving Average (ARIMA) and Long Short-term memory methods. This study uses the daily EUR / USD exchange rates from 2014 to March 2020. The data are used as the model to predict the value of the foreign exchange market in April 2020. The model obtained will be used for predictions in April 2020, where the RMSE values obtained from time series analysis (ARIMA) with a window size of 100 days and LSTM sequentially as follows 0.00527 and 0.00509. LSTM produces lower RMSE values than ARIMA. LSTM has better prediction results; this is because the LSTM has the ability to learn so that it can utilize a large amount of data while ARIMA cannot use it. ARIMA does not have the ability to learn even though given a large amount of data it gives poor forecasting results. The ARIMA prediction is the same as the values of the previous day.

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