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Contact Name
Sugeng Santoso
Contact Email
sugeng.santoso@mercubuana.ac.id
Phone
+6282132044774
Journal Mail Official
ti.jurnal@umm.ac.id
Editorial Address
Departement Industrial Engineering University of Muhammadiyah Malang Jl. Tlogomas No 246 Malang
Location
Kota malang,
Jawa timur
INDONESIA
Jurnal Teknik Industri
ISSN : 19781431     EISSN : 25274112     DOI : -
Dr. Saiful Anwar Malang is a state hospital has done it is job and function, but in 3rd class of pavilion room, the number of patient decrease dramatically. It is concerned with quality of this hospital. To answer this problem, research was done using Quality Function Deployment (QFD). Quality Function Deployment is a tool which design some needs include customers represented as a voice of customer and including some competitions and also groups some activities that usually called affinity graphic ang getting a benchmarking for it is competition. From the result analysis can be showed that main attribute for patience is a accuracy. And from House Of Quality can be found that getting a periodic meeting to evaluate this hospital and also increase a service can be made 20 concept
Articles 717 Documents
The Development of Halal Supply Chain Research in Indonesia: A Comparative Study Putri, Arinda Soraya; Susilo, Nazhifa Rahmi; Sakti, Ardhy Yuliawan Norma; Wicaksana, Danis Eka Prasetya
Jurnal Teknik Industri Vol. 25 No. 2 (2024): August
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol25.No2.97-118

Abstract

Halal products uphold the principles of halal throughout the entire supply chain, making managing the halal supply chain (HSC) crucial, especially for Muslim communities. Despite the importance of this topic, existing literature on halal supply chains remains limited, with most studies concentrating on the food industry. Notably, there is a significant research gap regarding the development of HSC research in Indonesia, the country with the largest Muslim population. This study aims to address this gap by conducting a comparative analysis of HSC research in Indonesia and globally. Utilizing Scopus as the data source, 355 studies on halal supply chains published between 2008 and 2024 were analyzed. A comparative study was then conducted to evaluate the development of HSC research in Indonesia based on various categories, including the number of publications, subject areas, authors, keywords, citations, paper quartiles, institutional affiliations, research objects, methods, and themes. The findings reveal that while Indonesia has made significant progress in HSC research, the research is still tiny compared to its Muslim population. These results highlight the need for further investment and focus on HSC research in Indonesia to match its global potential.
Supply Chain Risk Mitigation Based on The Integration of House of Risk and MOORA Puji, Ari Andriyas
Jurnal Teknik Industri Vol. 25 No. 2 (2024): August
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol25.No2.145-160

Abstract

Supply chains play a critical role in the operational success of organizations, impacting both costs and product quality. However, they are often exposed to various risks that can disrupt business processes. This research aims to identify supply chain risks and propose mitigation strategies using the House of Risk (HOR) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) methods. Through interviews, key issues were identified in a fiberglass company's supply chain, including raw material supply fluctuations, procurement cost variability, defective materials, inappropriate specifications, outdated technology, insufficient worker skills, and ambitious company targets. The novelty of this study lies in the application of MOORA, which introduces a correlation matrix for risk mitigation by considering both cost minimization and benefit maximization. The analysis identified 12 risk agents and 26 risk events, which were prioritized using HOR stage 2 with the MOORA method. The top preventive actions were ranked, providing actionable recommendations for companies to address supply chain risks more effectively. The findings of this research offer practical insights for companies in the fiberglass industry to enhance supply chain resilience by integrating cost and benefit considerations into their risk management strategies.
Agent-Based Modeling and Simulation for Farmer Decision Making Nurlina, Nila; Utomo, Dhanan S; Setiyawati, Tri Retno; Muqorobin, Masculine Muhammad
Jurnal Teknik Industri Vol. 25 No. 2 (2024): August
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol25.No2.119-130

Abstract

Shallots are a highly demanded, perishable commodity whose fluctuating prices pose significant risks to farmers, affecting their income stability. This research aims to model and simulate the selling decisions of shallot farmers using Agent-Based Modeling (ABM). The model represents the individual behaviors of farmers and buyers, focusing on decisions to either delay or immediately sell harvested shallots. Key variables such as market prices, inventory levels, and profit expectations were incorporated into the model. Primary data were collected from observations of shallot farmers in Nganjuk, East Java. In contrast, secondary data were sourced from the Indonesian Central Statistics Agency (BPS). The simulation results indicate farmers maximize their profits by selling shallots when the minimum sales profit margin reaches 20%. Farmers tend to postpone sales when market prices fall by drying the shallots, reducing market supply, and elevating prices. The study concludes that delaying sales can be an effective strategy to stabilize prices and enhance profitability, particularly when dried shallots command higher prices than fresh ones. These findings offer valuable insights for developing agricultural policies to optimize farmers' income while mitigating price volatility risks.
Multi-Objective Portfolio Optimization Using Hybrid Ant Colony Optimization and Compromise Programming Rahmalia, Dinita; Husenti, Nadya
Jurnal Teknik Industri Vol. 25 No. 2 (2024): August
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol25.No2.131-144

Abstract

The increasing complexity of stock trading requires effective portfolio management to optimize returns while minimizing risks. Portfolio selection is critical in determining the most suitable combination of stocks, aiming to maximize expected returns and minimize risk within a given investment limit. This study constructs a mathematical model for portfolio optimization using six different stocks, incorporating constraints such as expected return, risk, and available investment. Given the multi-objective nature of the problem, a hybrid approach is proposed, combining Compromise Programming (CP), Nadir Compromise Programming (NCP), and Ant Colony Optimization (ACO) to address both minimization and maximization objectives. The ACO algorithm is applied to minimize deviation variables, which serve as the fitness function in the optimization process. The results demonstrate the effectiveness of the hybrid method in selecting portfolios that achieve minimal deviation, providing an optimal balance between risk and return. This research offers valuable insights for investors by illustrating the trade-offs between risk and reward in stock selection, contributing to more informed decision-making in portfolio management.
Artificial Neural Network Model For Optimization of Forecasting Material Inventory: English Prastiya, Denny Suci; Wahyuni, Rossi Septy
Jurnal Teknik Industri Vol. 25 No. 2 (2024): August
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol25.No2.173-188

Abstract

The increasing competition in the fast-moving consumer goods (FMCG) industry leads to demand fluctuations, negatively impacting the accuracy of demand forecasts and determining optimal lot sizes in material inventory planning. Many companies struggle to adopt appropriate forecasting models, resulting in poor accuracy and higher material costs. This study aims to develop an integrated model for forecasting and material planning using simulation. The artificial neural network (ANN) method is proposed to improve forecasting accuracy, with performance evaluated through mean percentage error (MAPE), mean absolute deviation (MAD), and mean squared error (MSE). The forecast results are then applied to optimize material inventory using the economic order quantity (EOQ) model, considering warehouse capacity constraints. The EOQ model is applied to adjust lot sizes under time-varying demand. The findings highlight the importance of integrating forecasting with inventory planning to provide accurate demand predictions and optimal lot sizing, ultimately minimizing material costs in the FMCG industry. This research contributes to better decision-making in supply chain management by enhancing forecasting accuracy and inventory optimization.
Energy-Efficient Permutation Flow Shop Scheduling Problem: A Systematic Literature Review Utama, Dana Marsetiya; Primayesti, Meri Dines; Umamy, Sabila Zahra; Kholifa, Bunga Milenia Nur
Jurnal Teknik Industri Vol. 25 No. 1 (2024): February
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol25.No1.13-54

Abstract

Energy-efficient scheduling is an important problem in the industrial world because improper scheduling can increase energy consumption. One of the production scheduling problems is the Permutation Flow Shop Scheduling Problem (PFSP). This article tries to review research on energy-efficient PFSP to provide a comprehensive review of trends and research gaps in energy-efficient PFSP. A systematic literature review (SLR) was used to conduct this research survey, and 123 articles were collected from 2011-2023. This SLR classifies articles based on publication year, type, objective function, and optimization method used. The results of the literature review analysis show a significant increase every year for energy-efficient PFSP, and multi-objective problems are the dominant problems studied. Based on the analysis of solutions to solve energy efficient PFSP, metaheuristic procedures are the procedures that contribute the largest to solving energy efficient PFSP, and the objective function that is popularly used is to minimize total energy consumption. In addition to this, this study presents a gap research analysis and future research directions for energy-efficient PFSP.
Critical Indicators for Improving Compliance of Fuel Trading Business Entities in Indonesia Husniyadi, Ilham; Moeis, Armand Omar
Jurnal Teknik Industri Vol. 25 No. 1 (2024): February
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol25.No1.73-82

Abstract

Fuel oil is one of Indonesia's most dominant types of energy, making it important to have strict oversight and regulation of its supply and distribution. This research aims to identify compliance indicators for fuel trading business entities in the downstream oil and gas sector and develop guidelines to monitor and improve the level of compliance of these entities. The method used in this research is the Analytical Hierarchy Process (AHP). The results showed ten relevant compliance indicators: waste management, resource use, occupational accident rate, safety training, audits and inspections, regulatory violations, social and community contributions, stakeholder satisfaction, operational efficiency, and tax and financial compliance. Of the ten indicators, the highest weight is obtained from regulatory violations at 42%, followed by the work accident rate at 22%. These findings provide a strong basis for monitoring and improving compliance in the oil and gas trading business and supporting better and sustainable energy management in Indonesia.

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