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INDONESIA
Jurnal Teknik Industri
Published by Universitas Muhammadiyah Malang
ISSN : 19781431     EISSN : 25274112     DOI : -
Core Subject : Economy, Science, Engineering,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering
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
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Strategi dan Menejemen
Articles 5 Documents
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Search results for , issue "Vol. 24 No. 1 (2023): February" : 5 Documents clear
Novel Heuristic Algorithm for Flexible Job Shop Scheduling based on the Longest Processing Time Rules to Minimize Makespan Eka Pakpahan; Kenneth David Sumarna
Jurnal Teknik Industri Vol. 24 No. 1 (2023): February
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol24.No1.17-30

Abstract

This research examined the scheduling of jobs with multiple stages unto identical parallel machines to minimize the makespan. The work is motivated by a Flexible Manufacturing System case that produces various parts and has multiple machining centers. Early research towards this system proposed a stage-by-stage independent scheduling, resulting in a non-optimal solution. This study aimed to create a better solution for the system by developing a novel heuristic algorithm based on the classical longest processing time algorithm and simultaneously considering processing time for all stages when deciding the job sequencing and job-machine allocation. The algorithm is defined as Modified LPT for Multiple Identical Machine with Multi-process Capability (M-LPT MIMMPC). We performed a numerical experiment to assess the algorithm's performance by incorporating various cases. We concluded that the resulting makespans are always better than LPT's theoretical bound for parallel machine scheduling. In some cases, it successfully gave an optimal value. Although the experiment scope was still limited, the algorithm showed promising performance results.
Development of Customer Loyalty Model on Online Transportation Service: A Case Study in Indonesia Budhi Prihartono; Karina Rizky Ismantia; Fidruzal Fahlevi
Jurnal Teknik Industri Vol. 24 No. 1 (2023): February
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol24.No1.1-16

Abstract

The impact of technology on public transport has led to a new online transportation service. Its emergence makes the competition increasingly competitive. Therefore, customer loyalty becomes an important aspect of winning the competition. This research analyzed the effect of customer service, service delivery, onboard experience, public image, service value, and customer satisfaction on customer loyalty to online transportation. 517 respondents were obtained and divided into two groups: captive rider and choice rider. Data processing is carried out using a multigroup SEM technique. The results showed that there was a significant moderation effect of the different characteristics of users. In the captive rider group, onboard experience and service value did not affect customer satisfaction, and service value did not affect customer loyalty. Customer satisfaction influenced customer loyalty, and the effect was more robust than the choice rider group. In the choice rider group, the public image did not affect customer satisfaction, but service value influenced customer loyalty. Factors proven to influence customer loyalty significantly can be developed by companies to improve their competitive advantage in an increasingly competitive market of online transportation services.
Optimization Multi-Item Lot Sizing Model involve Transportation and Capacity Constraint under Stochastic Demand using Aquila Optimizer Dana Marsetiya Utama; Selvia Rubiyanti; Rahmat Wisnu Wardana
Jurnal Teknik Industri Vol. 24 No. 1 (2023): February
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol24.No1.31-50

Abstract

Inventory issues are often a major concern as they significantly impact operating costs. Lot sizing is one of the key decisions in managing inventory. However, in a real context, the demand for each item is often uncertain. It is supplied from the same supplier, requiring product orders to be placed in the same period. In addition, limited vehicle capacity and transportation costs are important factors to consider in making multi-item lot sizing decisions. The purpose of this study is to propose a new inventory model multi-item lot sizing model involving transportation cost and capacity constraints under stochastic demand. The decision variables involved in the model are each item's ordering cycle and safety factor with the objective function of minimizing the total inventory cost. To optimize the inventory model, this study also offers the advanced procedure of the Aquila Algorithm. This study also presents sensitivity analysis to the appropriate policy for optimizing the multi-item lot-sizing inventory problem involving transportation cost and capacity constraint under stochastic demand.
Sustainable Layout Design Based on Integrated Systematic Layout Planning and TOPSIS: A Case Study Meiliza Dresanala; Shanty Kusuma Dewi; Dana Marsetiya Utama
Jurnal Teknik Industri Vol. 24 No. 1 (2023): February
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol24.No1.51-64

Abstract

This research applies the concept of sustainable layout in the manufacturing industry by incorporating social, environmental, and economic aspects in the production process. The main objective of this research is to design a sustainable layout for the plastic packaging manufacturing industry. The approach utilizes the TOPSIS method to select an Activity Relation Chart (ARC) integrated with a systematic Layout Planning procedure. A case study is presented on an industry that produces plastic packaging in Indonesia. The results show that the proposed sustainable layout design significantly reduces the material handling distance compared to the initial layout. These results confirm that the Systematic Layout Planning approach and TOPSIS method have great potential in designing layouts that integrate sustainable principles effectively in manufacturing environments.
A No-Idle Flow Shop Scheduling using Fire Hawk Optimizer to Minimize Energy Consumption Devisa Restiana Wati; Ikhlasul Amallynda
Jurnal Teknik Industri Vol. 24 No. 1 (2023): February
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol24.No1.65-80

Abstract

The current energy crisis is a pressing global challenge, with the industrial sector accounting for half of global energy consumption. Scheduling is considered one of the potential methods to reduce energy consumption. This article introduces the Fire Hawk Optimizer (FHO) algorithm to solve the no-idle flow shop scheduling problem to minimize overall energy consumption. FHO organizes the job sequence in no-idle flow shop scheduling for reduce energy consumption. This research investigates the use of different machine speed levels, namely slow, fast, and normal, based on case data of manufacturing industries in Indonesia. The results of this study compare the performance of the FHO algorithm with the Adaptive Integrated Greedy (AIG) heuristic method and compare it with the Grey Wolf Optimizer (GWO) algorithm. The experimental results showed that total energy consumption tends to be high when processed at high speed. Conversely, low-speed results in lower energy consumption but requires longer processing time. The comparison results show that the Fire Hawk Optimizer is more efficient in reducing total energy consumption than the AIG heuristic method. Meanwhile, the FHO algorithm performs comparably to the GWO algorithm and completes enumeration. These findings confirm that the proposed procedure can be an alternative to the scheduling optimization process.

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