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Jurnal Optimasi Sistem Industri

JOSI
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Published by Universitas Andalas

ISSN : 20884842 EISSN : 24428795 DOI : -

Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mechanical Engineering

Jurnal Optimasi Sistem Industri (JOSI) is a peer-reviewed journal that is published periodically (April and October) by the Department of Industrial Engineering, Faculty of Engineering, Universitas Andalas, Padang.

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Articles 8 Documents

Search results for , issue "Vol. 19 No. 2 (2020): Published in November 2020" : 8 Documents clear

A Hybrid Simulation Study to Determine an Optimal Maintenance Strategy Ig. Jaka Mulyana; Ivan Gunawan; Yunia Vera Angelia; Dian Trihastuti
Jurnal Optimasi Sistem Industri Vol. 19 No. 2 (2020): Published in November 2020
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

With the increasing complexity of the process industry, having excellent maintenance management is essential for manufacturing industries. Various parts that interact and interdependent with each other make a well-planned maintenance strategy is one of the major challenges facing by industry. The whole system could be interrupted just simply because of the failure of a component. Therefore, a review of a maintenance strategy must be done from a system perspective. It is suggested that the optimal preventive maintenance time interval is not only determined by the lowest maintenance cost of each machine but also its impact on the whole system. Two main indicators that can accommodate the system perspective are reliability and revenue. A large number of machines and the array of machines can be synthesized in the reliability indicator. Moreover, the creation of maximum revenue is always the main goal for a business. The best maintenance strategy will be determined from the revenue obtained by a process industry. The process industry discussed in this study is a flour mill which is very well known in Surabaya. This study applied a hybrid simulation to solve this problem. Monte Carlo simulation was used to observe the machine individually and the results are reviewed using the application of System Dynamics. Three improvement scenarios were proposed in this simulation study. Scenario 2 was chosen as the best scenario because it was able to generate the highest revenue at the end of the period. Scenario 2 recommends setting the preventive maintenance time interval considering resource availability.

The Effect of Digital Talent on Individual Innovation Behavior, Skills of Revolution Industry 4.0 as Mediator Variables Riri Nofrita; Insannul Kamil; Jonrinaldi Jonrinaldi; Berry Yuliandra; Irsyadul Halim
Jurnal Optimasi Sistem Industri Vol. 19 No. 2 (2020): Published in November 2020
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

In the face of the Revolution industry 4.0, global connection, artificial intelligence, and automation have disrupted technology. This made the industrial world's development in work competition, not linear and even created new jobs. Digital talent and innovation are needed to face the world of work. This study discusses the construct effect between digital talent, individual innovation behavior, and Skills Revolution Industry 4.0, and the effect of Skills Revolution Industry 4.0) as a mediator to digital talent constructs' relationship. Data collection is obtained directly (face to face). Samples were previously clustered by sampling technique. Questionnaires use the Likert Scale. Then, the data gotten were processed by SEM-PLS with Software 3.8.2. The result showed that digital talent has a positive effect on individual innovation behavior. This meant that skill of revolution industry 4.0 as a construct mediator was successful. The stronger digital talent influences, the stronger individual innovation behavior influences, and it is accelerated with revolution industry skills 4. This study proposes a model to build mastery of digital talent and individual innovation behavior of Universitas Andalas students through the mastery of skills of revolution 4.0 as a mediator. This research can pave the way to improve students' readiness in facing the world of revolution 4.0, one of which is in the field of digital innovation.

Recycling Solid Waste of Coconut Oil Industry: A Response Surface-Goal Programming Approach Dwi Agustin Nuriani Sirodj; Ivan Gunawan
Jurnal Optimasi Sistem Industri Vol. 19 No. 2 (2020): Published in November 2020
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Waste minimization is a key success factor to achieve sustainability, including in the edible oil industry. One type of solid waste produced substantially in this industry is spent bleaching earth (SBE), which comes from a mixture of bleaching earth (BE) and activated carbon (CA) used in the edible oil refining process. SBE that is recycled through a heating process is known as heat regenerated SBE (HRSBE). The process is influenced by two factors as stated in previous studies: temperature and time. In the current study, we report the results of experiments to find the optimal combination of temperature and time in restoring the absorbent quality of SBE by observing four quality parameters: colors (red and yellow), Free Fatty Acid (FFA), and Peroxide Value (PV). The current study uses Response Surface Methodology (RSM) to design the experiments and to find the equations of the relationship between the factors for each response; as well as Goal Programming (GP) to find the most optimal combination of factors in order to achieve aggregated quality targets. The findings show that 3.414 hours of heating at a temperature of 151.64oC allow HRSBE to produce coconut oil in accordance with the expected quality targets.

Supply Chain Performance Measurement Framework for Construction Materials: Micro Meso Macro Moh Nur Sholeh; Mochamad Agung Wibowo; Naniek Utami Handayani
Jurnal Optimasi Sistem Industri Vol. 19 No. 2 (2020): Published in November 2020
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Productivity is a challenge in the construction industry, commonly initiated by fragmentation. In addition, some work levels have been identified, including the micro, meso, and macro. However, the construction supply chain is one of the possible solutions adopted to increase productivity. The purpose of this study, therefore, is to develop a framework for measuring supply chain construction performance at the micro, meso, and macro levels. These respective stages are tiered from the bottom to the top level as a supply chain management concept. Furthermore, a design for the supply chain performance measurement framework is created, followed by formulation with KPI, and the consequent application in the project. Therefore, performance is evaluated based on the construction materials, as a large resource. The results identified the supply chain performance at the micro-level as the basis for possible measures between contractor and supplier, using the SCOR. However, the emphasis was made on the strength of construction companies with large suppliers at the meso level. Meanwhile, the macro-level includes the accumulation of related measurements from micro as well as meso, and are consequently used to define the relationship between construction actors at the national level.

Cover & Preface JOSI Vol. 19(2) 2020 Hilma Zadry
Jurnal Optimasi Sistem Industri Vol. 19 No. 2 (2020): Published in November 2020
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

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Sequential Routing-Loading Algorithm for Optimizing One-Door Container Closed-Loop Logistics Operations Paulina Kus Ariningsih; Titi Iswari; Kevin Djoenneady Poetra; Yoon Mac Kinley Aritonang
Jurnal Optimasi Sistem Industri Vol. 19 No. 2 (2020): Published in November 2020
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

One-door container type of vehicle is the main tool for urban logistics in Indonesia which may take the form of truck, car, or motorcycle container. The operations would be more effective when it is performed through pickup-delivery or forward-reverse at a time. However, there is difficulty to optimize the operation of routing and container loading processes in such a system. This article is proposing an improvement for algorithm for sequential routing- loading process which had been tested in the small datasets but not yet tested in the case of big data set and vehicle routing problem with time windows. The improvement algorithm is tested in big data set with the input of the vehicle routing problem with time windows (VRP-TW) using the solution optimization of the Simulated Annealing process with restart point procedure (SA-R) for the routing optimization and Genetic Algorithm (GA) to optimize the container loading algorithm. The large data sets are hypothetical generated data for 800-2500 single-sized products, 4 types of container capacity, and 100-400 consumer spots. As result, the performance of the proposed algorithm in terms of cost is influenced by the number of spots to be visited by the vehicle and the vehicle capacity. Limitations and further analysis are also described in this article.

The Influence of Stress on Industrial Operator’s Physiology and Work Performance Kamarulzaman Mahmad Khairai; Auditya Purwandini Sutarto; Muhammad Nubli Abdul Wahab
Jurnal Optimasi Sistem Industri Vol. 19 No. 2 (2020): Published in November 2020
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Elevated stress has been widely associated with physical and physiological threats as well as reduced work performance. However, there is still a lack of studies that investigate whether stress influences concurrently physiological and objective work performance. The purpose of this study is to examine whether workers’ level of stress or negative emotional symptoms correlates with their physiological coherence and work performance. Eighteen female operators who reported high severity levels of stress, assessed using the Depression, Anxiety, and Stress Scale (DASS-42) were categorized as the risk group. The comparison group was formed by randomly selecting 18 of 99 female workers who had significantly lower DASS scores. Both participants attended one session of physiological measurement. Their work performance was observed by calculating their cycle time completing a product during five workdays. A significant difference in HRV between the two groups was also found in physiological and work performance measures. The results showed that workers in the risk group obtained significantly lower coherence levels and longer work cycle time than the control participants, indicating that negative emotional symptoms were parallel with physiological coherence and work performance. However, a weak correlation was found between work performance and negative emotional symptoms as well as physiological coherence. Despite the study limitations, our findings support to evidence the more complete picture of how stress affects female worker’s physiology and work performance, suggesting a need to implement effective workplace stress intervention. Further study is needed to be conducted among different group characteristics such as male and occupational settings.

A Decision Support System to Achieve Self-Sufficiency of Soybean (Case: Central Java Province, Indonesia) Muhammad Hisjam; Nancy Octyajati; Wahyudi Sutopo; Ahad Ali
Jurnal Optimasi Sistem Industri Vol. 19 No. 2 (2020): Published in November 2020
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Soybean self-sufficiency in Central Java Province is a problem that is difficult to realize at this time. As an important commodity, self-sufficiency becomes a serious concern for the government. Supply chain management of soybean is related to the integration of supply, demand, and distribution of soybean. The characteristics of entities involved in the soybean supply chain are complex, dynamic, and probabilistic that make the problem cannot be solved using an analytical model and it becomes too risky for trial and error. A suitable tool is using a simulation model. This paper deals with developing a Decision Support System (DSS) using a simulation model that will assist the government in adopting policies in order to achieve self-sufficiency of soybean and the improvement of farmer's welfare. DSS will help decision-makers to try various scenarios of policy in an easy way. The method was started with developing model components, then decision components, and next creating user interfaces. The simulation and system modeling is created by using Powersim software with the intent to obtain the simulation and single document interface (SDI) of the supply chain model. The result shows that land expansion policy is a top priority for realizing food self-sufficiency while increasing productivity and reducing costs of agricultural activities are the main priorities for improving the welfare of farmers.

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Rika Ampuh Hadiguna

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Home Page

OAI Link

Editorial Team

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Reviewer

Google Scholar

Contact Name Rika Ampuh Hadiguna

Contact Email hadiguna@ft.unand.ac.id

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Journal Mail Official hadiguna@ft.unand.ac.id

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Location Kota padang, Sumatera barat INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Rika Ampuh Hadiguna

Contact Email
hadiguna@ft.unand.ac.id

Phone
-

Journal Mail Official
hadiguna@ft.unand.ac.id

Editorial Address
-

Location
Kota padang,

Sumatera barat

INDONESIA