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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 69 Documents
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Analysis of marketing strategy at setia stores using ahp, clustering, and ar-mba method Ibrahim, Faisal; Putra, Bagas Swardhana; Azhra, Fariza Halidatsani; Fadhlurrohman, Najib
International Journal of Industrial Optimization Vol 2, No 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i2.4369

Abstract

A company can survive and thrive when the strategies and processes applied in its business are correct. One of the processes in determining strategy in decision making. The owner of Setia Store has difficulty in choosing a marketing strategy. The product layout shows this in the Setia Store, which confuses customers. Setia Store also rarely offers a promotion, making it difficult to compete with competitors. This study aims to help Setia Store increase sales by determining the right marketing strategy. To determine the right marketing strategy, there are three methods developed. First of all, the analytical hierarchy process (AHP) is employed to find the customer priorities. Then, clustering is proposed to find potential marketing targets that have similar characteristics from the results of the AHP method. Third, association rule-market basket analysis (AR-MBA) is developed to find the best rules for product marketing strategy. The first method shows that the housewives (EV=0.6270) are Setia Store's priority customers from the three methods. Second, cluster 3 (which has three characteristics in common) is a very potential target market. Third, the best rule is to buy products from departments 2 and 3 (Confidence 60%, Support 12%). From these results, the right marketing strategy is to create a buy 1 get 1 promo banner or label for products that are rarely purchased, such as household appliances. Then, create a catalog by bringing together frequently purchased products such as spices and food ingredients. Finally, improve the layout by bringing the departmental shelves closer to frequently purchased products.
The hybrid design of supervised learning algorithm for design and development in classifications a defect in clay tiles Prasetio, Murman Dwi; Xavier, Rais Yufli; Rachmat, Haris; Wiyono, Wiyono; Atmaja, Denny Sukma Eka
International Journal of Industrial Optimization Vol 2, No 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i2.4449

Abstract

The strength of the company's competitiveness is needed because the current industrial development is very rapid. It is necessary to maintain the quality and quantity of the products produced according to company standards.  One of the companies that must maintain the quality and quantity is PT. XYZ is a clay tile company. The classification of products used by this company to maintain good quality is three classes: good tile, white stone tile, and cracked tile. However, quality control based on classification still uses the traditional way by relying on sight.  It can increase errors and slow down the process. It can be overcome with artificial visual detectors. It is a result of the rapid development of automation. So to detect defects, this research can use image preprocessing, supervised learning algorithms, and measurement methods.  Support Vector Machine (SVM) is used in this study to perform classification, while feature extraction on clay tiles used the Local Binary Pattern (LBP) method. The algorithm is made using python, while for image retrieval, raspberry pi is used. The linear kernel on the SVM algorithm is used in this study. The conclusion in this study obtained 86.95% is the highest accuracy with a linear kernel. It takes 10.625 seconds to classify.
A dai-liao hybrid conjugate gradient method for unconstrained optimization Salihu, Nasiru; Odekunle, Mathew Remilekun; Waziri, Mohammed Yusuf; Halilu, Abubakar Sani; Salihu, Suraj
International Journal of Industrial Optimization Vol 2, No 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i2.4100

Abstract

One of todays’ best-performing CG methods is Dai-Liao (DL) method which depends on non-negative parameter  and conjugacy conditions for its computation. Although numerous optimal selections for the parameter were suggested, the best choice of  remains a subject of consideration. The pure conjugacy condition adopts an exact line search for numerical experiments and convergence analysis. Though, a practical mathematical experiment implies using an inexact line search to find the step size. To avoid such drawbacks, Dai and Liao substituted the earlier conjugacy condition with an extended conjugacy condition. Therefore, this paper suggests a new hybrid CG that combines the strength of Liu and Storey and Conjugate Descent CG methods by retaining a choice of Dai-Liao parameterthat is optimal. The theoretical analysis indicated that the search direction of the new CG scheme is descent and satisfies sufficient descent condition when the iterates jam under strong Wolfe line search. The algorithm is shown to converge globally using standard assumptions. The numerical experimentation of the scheme demonstrated that the proposed method is robust and promising than some known methods applying the performance profile Dolan and Mor´e on 250 unrestricted problems.  Numerical assessment of the tested CG algorithms with sparse signal reconstruction and image restoration in compressive sensing problems, file restoration, image video coding and other applications. The result shows that these CG schemes are comparable and can be applied in different fields such as temperature, fire, seismic sensors, and humidity detectors in forests, using wireless sensor network techniques.
Simulation of trends in the use of e-payment using agent based models Elanjati Worldailmi; Ismianti Ismianti
International Journal of Industrial Optimization Vol. 1 No. 1 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i1.1276

Abstract

Bank Indonesia (BI) as the central bank in Indonesia has launched a movement to use non-cash instruments in conducting transactions on economic activities. The majority of Indonesian people are increasingly ready to trade without cash or cashless society. The country's economic policy factors, the availability of various non-cash payments, and online sales and purchases, encourage the tendency to use non-cash transactions (e-payment). One way to find out these trends is to use a model. Models can help understand and explain real phenomena more easily and efficiently than directly observing. One model that can be used is Agent Based Modeling and Simulation (ABMS). By using ABMS, the development of models with complex behaviors, dependencies, and interactions can be developed more easily. ABMS is able to describe processes, phenomena, and situations. In this study, the factors that influence the tendency to use e-payment are obtained from various references. From these factors, then created a scenario as a sub-purpose of this model. In simulations using ABMS, detailed descriptions explained based on ODD Protocol elements can be more easily understood and complete. ODD systematically evaluates a model. The advantage is that ODD can improve the accuracy of model formulas and make the theoretical basis more visible.
Hybrid genetic-tabu search algorithm to optimize the route for capacitated vehicle routing problem with time window Mohammad Deni Akbar; Rio Aurachmana
International Journal of Industrial Optimization Vol. 1 No. 1 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i1.1421

Abstract

Optimization of transportation and distribution costs is one of the important issues in the supply chain management area. It is caused by their large contribution to the logistics costs that can reach up to 40%. Thus, choosing the right route is one of the efforts that can be done to resolve the issue. This study aims to optimize the capacitated vehicle routing problem with time windows (CVRPTW) for mineral water company distributor with pick-up and delivery problem. To achieve the aim, this study used hybrid algorithm, Genetic Algorithm (GA) and Tabu Search Algorithm (TS). The selection of this hybrid algorithm is due to its capability in minimizing travel distance. The result of this study shows that not only the algorithm has successfully reduced the existing route but also predicted the optimum number of homogenous fleet. By running the algorithm, this study concludes that the number of the optimum routes for this study can be reduced for up to 15.99% than the existing route.
The best route determination using nearest neighbor approach Nafia Rahma; Annie Purwani; Dwi Nita Febriyanto
International Journal of Industrial Optimization Vol. 1 No. 1 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i1.1423

Abstract

This research constitutes an application of heuristic optimization using the nearest neighbor (NN) method. It is a method used to design a route based on the next closest distance. The case here is the garbage freight of Yogyakarta City which becomes one of the Environmental Services Department duties. The sector of this research object is Malioboro-Kranggan because it has the highest number of TPS locations. There are 34 TPS locations, and 2 depots with an average volume of total garbage are 197 m3/day. Several alternative routes have resulted because the same distance was found when deciding the next distance (TPS 26 and TPS 31). The best alternative was determined based on the best scenario parameter of total mileage and operational time. The first scenario chose the garbage volume that is close to the remaining capacity, meanwhile, the second scenario chose the smallest garbage volume. At TPS 27, an alternative with the same closest distance appeared again (TPS 15 and TPS 18). Hence, the whole algorithm results in four alternative decisions. The first alternative results 13.59 hours as the total time and 40.092 km as the total distance, the second results 13.50 hours with 40.315 km, the third results 13.57 hours with 41.393 km, and the fourth results 13.803 hours with 40.41 km. The best alternative goes to the first alternative based on the parameter set before. It means that the scenario taken is by choosing the TPS with the closest remaining volume of the vehicle.
Optimizing shipping routes to minimize cost using particle swarm optimization Annur Rahman; Hayati Mukti Asih
International Journal of Industrial Optimization Vol. 1 No. 1 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i1.1605

Abstract

Product shipping is important in the economic process in the company. Efficient product shipping routes should provide low transportation costs. This study based on a case company of CV. Kayana, a distributor of “Sari Roti”, has 4 motorbikes and 2 cars. Each vehicle has their own shipping routes. Nowadays, high distance for each route results on high transportation cost. Therefore, the objective of this study to minimize the distance and cost of product shipping by developing shipping algorithm using Particle Swarm Optimization (PSO) for Traveling Salesman Problem (TSP). The MATLAB software was employed to solve this problem. The solution is obtained by varying the amount of particles and number of iterations. Experimental results proved that the developed PSO is enough effective and efficient to solve shipping routes problem. The results show the proposed model have lower distance and transportation cost. It helps the company in determining the routes for product shipping with minimum transportation cost.
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.

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