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INDONESIA
Jurnal Sistem dan Manajemen Industri
Published by Universitas Serang Raya
ISSN : 25802887     EISSN : 25802895     DOI : -
Core Subject : Engineering,
Engineering Industrial & Manufacturing Engineering Transportation
This journal aims to publish the results of research in the field of Industrial Engineering is published twice a year, managed by the University of Serang Raya. The scope of Sciences covers Operations Research, Manufacturing System, Industrial Management, Ergonomics and Work System, Logistics and Supply Chain Management, and other scientific studies in accordance with scope field of Industrial Engineering research.
Arjuna Subject : -
Articles 170 Documents
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Penggunaan Teknik Analisis Data Deep Learning dalam Pengoptimalan Pemeliharaan Terrencana Berkapasitas Muhammad Ridwan Andi Purnomo
Jurnal Sistem dan Manajemen Industri Vol. 6 No. 2 (2022): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (797.846 KB) | DOI: 10.30656/jsmi.v6i2.5076

Abstract

Manufacturing systems must be supported by the availability of materials, a streamlined production process and a prepared production line to achieve the production target. In a mass customization manufacturing system, the number of machines required for customization is relatively small. Conse-quently, maintenance on critical machines will impact this manufacturing system the most. Two types of maintenance strategies are implemented: corrective and preventive maintenance. The corrective maintenance requires more resources since the time and cost to repair the breakdown machine will be higher due to fatal failure. For the management to consider preventive maintenance while the binding machines are still operational, it must be equipped with a deep analysis demonstrating that fewer resources will be required. This paper discusses two deep analyses: accurate prediction of the binding machines' breakdown based on Mean Time Between Failure (MTBF) data using a deep learning data analytics technique and optimizing the maintenance total cost in the available capacitated time. The findings and results of this paper show that the proposed deep learning data analytics technique can increase the MTBF prediction accuracy by up to 66.12% and reduce the total maintenance cost by up to 4% compared with the original model.
Multi-objective optimization model of cutting parameters for a sustainable multi-pass turning process Wahyu Widhiarso; Ibnu Abdul Rosid; Rieska Ernawati
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 1 (2023): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i1.5747

Abstract

The turning process involves the linear removal of material from the work-piece and requires a relatively high amount of energy. The high energy consumption of the machining process increases carbon emissions, which affects the environment. Moreover, production costs will rise as the cost of energy rises. Energy savings during the machining process are crucial for achieving sustainable manufacturing. In order to determine and optimize the cutting parameters, this study creates a multi-pass turning processes optimi¬zation model. It considers cutting speeds, feed rates, and depth of cut. In this study, the model uses multi-objective optimization by incorporating three objective functions: processing time, energy consumption and product¬ion costs. OptQuest completed the proposed model in Oracle Crystal Ball software, then normalized and weighted the sum. Ordering preferences, the Multi-Objective Optimization based on Ratio Analysis (MOORA) approach is utilized. It ranks items based on their higher priority values. This paper provides a numerical example to demonstrate the application of an optimi¬zation model. Based on the preference order ranking results, the optimal values for three objective functions are as follows: total processing time of 4.953 min, the total energy consumption of 5.434 MJ, and total production cost of 395.21$.
Technology content assessment for Indonesia-cable based tsunameter development strategy using technometrics model Gani Soehadi; Lesti Setianingrum; Sasono Rahardjo; I Wayan Wira Yogantara; Edhi Purnomo; Michael Andreas Purwoadi; Irawan Santoso
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 1 (2023): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i1.5748

Abstract

This research aims to calculate the value of the Technology Contribution Coefficient (TCC) and determine the priority of technology component improvement in the development of the Indonesia-Cable Based Tsunameter (INA-CBT) Tsunami Early Warning System (TEWS) conducted by the National Research and Innovation Agency (BRIN) Research Center for Electronics (RCE). In this study, the Technometrics model is used to calculate the technology contribution of technology components and TCC, while Analytical Hierarchy Process (AHP) is used to calculate the value of the technology contribution intensity of technology components. The results showed that the TCC value of the RCE is 0.55 (Good). With the state-of-the-art value of 1, the RCE still has the opportunity to make improvements, especially on Infoware components with the lowest contribution value, to increase TCC. In calculating the technology contribution intensity, Infoware obtained the highest score of 0.447 compared to other technology compo­nents, therefore Infoware needs to be prioritized for improvement so that it is expected that the management of RCE can increase the quality and accuracy of the engineering design and simulation stage because it is a critical point in the development of INA-CBT.
Disaster risk analysis of technological failure of industrial estate: a case study: Turniningtyas Ayu Rachmawati; Dwi Rahmawati
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 1 (2023): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i1.4673

Abstract

The world has agreed on reducing disaster risks through Sendai Framework for Disaster Risk Reduction (SFDRR) 2015–2030. Efforts to reduce disaster risks are one way to attain Sustainable Development Goals related to "sustainable cities and communities." The first points of disaster risk reduction priorities inscribed in the SFDRR 2015–2030 incorporate disaster risk studies. While studies on natural disaster risks have been widely conducted, non-natural (manmade) disaster risk studies are relatively scant, parti­cularly for technological failure disasters. In this paper, the author investigates the levels of technological failure disaster risks in Gresik Regency, Indonesia, one of the National Strategic Areas in East Java Province. This study employs a disaster risk analysis encompassing aspects of hazard and vulnerability through map overlays with the help of a Geo­graphical Information System (GIS) to identify areas with risks of techno­logical failure. Results illustrate that a high risk is predominantly spread in areas with high hazards, which is 60 m radius of the industrial area. The findings in this study may help shed light on the hazards that may arise due to technological failures that span not only around the source of hazard, i.e., the industrial areas, but also beyond them, and also conclude that the higher the disaster risk is, the higher the vulnerability of an area will be.
Digital strategy for improving resilience of micro, small, and medium enterprises Issa Dyah Utami; Trisita Novianti; Fachrizal Setiawan
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 1 (2023): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i1.6087

Abstract

The COVID-19 pandemic impacted several small and medium-sized enter­prises (SMEs) in Indonesia. The viability of some SMEs' business opera­tions was disturbed, especially those who create non-essential goods like carving. The sales have decreased by up to sixty per cent, causing reduced levels of income and the termination of numerous workers. SMEs in Indonesia are highly considered because businesses are one of the country's most significant economic contributors. This research proposes a strategy for SMEs to improve the resilience of business operations of the SMEs. The K-means method was used to investigate three groups of SMEs: micro, small, and medium. Changes in the SME class before and after the pandemic are investigated through changes in the values of the variables in the SME profile. Then the SWOT method is used to identify internal and external factors with the highest weight, which can be used as a basis for developing strategies to increase the resilience of SMEs. Furthermore, the TOPSIS method determines the best plan for dealing with the new digital era. The result shows that the W-T strategy to utilize social media can be prioritized based on the criteria that significantly impact SMEs' product sales and business resilience.
Telecommunication service quality analysis using integration of SIPA and modified Kano Hanny Kanavika Rizky Munawar; Annisa Kesy Garside; Adhi Nugraha; Amelia Khoidir
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 1 (2023): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i1.5530

Abstract

This article investigates the integrated approach of the Simultaneous Impor­tance-Performance Analysis (SIPA) model and the modified Kano model to evaluate and prioritize service attributes for telecommunication companies in Indonesia. The study is based on the demographic profiles and usage patterns of 74 respondents. The results demonstrate that the SIPA and Kano models can provide valuable insights for identifying priority areas and effective strategies for improving service quality. Specifically, the SIPA model helps to compare competitor performance and identify important service attributes. In contrast, the modified Kano model facilitates a dynamic cycle of service attribute evaluation to inform managerial strate­gies. This article contributes by highlighting the potential of the proposed ap­proach to offer valuable insights to telecommunication companies seeking to enhance their service offerings and remain competitive in a con­stantly evolving market.
Mix method analysis for analyzing user behavior on logistic company mobile pocket software Satria Fadil Persada; Farid Afandi; Anak Agung Ngurah Perwira Redi; Reny Nadlifatin; Yogi Tri Prasetyo; Adji Candra Kurniawan
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 1 (2023): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i1.5937

Abstract

The present study emphasizes mixed-method analysis, integrating the partial least square structural equation model (PLS-SEM) and customer journey for mobile pocket office improvement in logistic XYZ company. The extension of the unified theory of acceptance and use of technology (UTAUT 2) model by incorporating perceived risk (PR), personal innovativeness (PI), and trust (TR) variables are used. The sample for this study consisted of 243 res­pondents. Based on the results of the PLS-SEM analysis, two of the eleven tested hypotheses were determined to be rejected. In application usage, the proposed model effectively explained 85.7 per cent of the influence on beha­vioral intention (BI) and 72.1 per cent on use behavior (UB). The customer journey mapping (CJM) investigation's findings show that fluctuations in the use of mobile pocket office technology in the field are generally brought on by a lot of data entry, sluggish internet connections, and overworked field operations. The XYZ company may acquire sugges­tions and knowledge for developing further applications due to this inquiry.
A modified Aquila optimizer algorithm for optimization energy-efficient no-idle permutation flow shop scheduling problem Dana Marsetiya Utama; Nabilah Sanafa
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 2 (2023): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i2.6446

Abstract

Increasing energy consumption has faced challenges and pressures for modern manufacturing operations. The production sector accounts for half of the world's total energy consumption. Reducing idle machine time by em­ploying No-Idle Permutation Flow Shop Scheduling (NIPFSP) is one of the best decisions for reducing energy consumption. This article modifies one of the energy consumption-solving algorithms, the Aquila Optimizer (AO) algo­rithm. This research contributes by 1) proposing novel AO procedures for solving energy consumption problems with NIPFSP and 2) expanding the literature on metaheuristic algorithms that can solve energy consumption problems with NIPFSP. To analyze whether the AO algorithm is optimal, we compared by using the Grey Wolf Optimizer (GWO) algorithm. It com­pares these two algorithms to tackle the problem of energy consumption by testing four distinct problems. Comparison of the AO and GWO algorithm is thirty times for each case for each population and iteration. The outcome of comparing the two algorithms is using a t-test on independent samples and ECR. In all case studies, the results demonstrate that the AO algorithm has a lower energy consumption value than GWO. The AO algorithm is there­fore recommended for minimizing energy consumption because it can produce more optimal results than the comparison algorithm.
Optimisation-in-the-loop simulation of multi products single vendor-multi buyers supply chain systems with reactive lateral transhipment Muhammad Ridwan Andi Purnomo
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 2 (2023): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i2.6495

Abstract

Considering that batik is one of the most popular products in Indonesia, it is important to analyse the supply chain system for batik products. In reality, the supply chain system for batik products enables orders between buyers to receive products more rapidly, allowing them to anticipate stock outs and obtain lower ordering costs than when ordering from vendors. It is referred to as reactive lateral transshipment. This paper discusses the development of a simulation-based stochastic optimisation model for a batik product supply chain system with multiproducts and single vendor-multi buyers. The utilised solution searching algorithm is a modified Genetic Algorithms (GA) executed in-loop with the developed simulation-based stochastic model. The results demonstrate that the proposed modified GA is able to provide a global optimum solution, allowing the proposed simulation-based stochastic model to reduce the joint total cost (JTC) of the investigated supply chain system by up to 19% when compared to the local optimisation model in each supply chain party.
Integration models of demand forecasting and inventory control for coconut sugar using the ARIMA and EOQ modification methods Siti Wardah; Nunung Nurhasanah; Wiwik Sudarwati
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 2 (2023): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i2.6500

Abstract

Inventory control is critical because the inability to overcome inventory problems causes unpreparedness to meet consumer demand. MSMEs Bekawan Agro Coconut Sugar, independently around 35% -70%, cannot meet consumers' demand for coconut sugar, so an inventory control model is needed. Inventory control models must integrate with demand forecasting as an inventory control input. This study aims to integrate the demand fore­casting model with the inventory control model. The method used for demand forecasting is ARIMA. The inventory control model uses a modi­fied EOQ hybrid method because coconut sugar products have a shelf life; they also use coconut sap as raw material, which must be processed to prevent fermentation. The research results show that demand forecasting for one year ahead is a total of 10,310.82 Kilograms with an economic lot size of 120 Kilograms and a reorder point when the inventory position is 30 Kilograms. Daily production of 30 kilograms requires 210 litres of coconut sap/per day. The amount of sap needed requires 105 coconut trees / per day. Arrival time of coconut sugar at the storage warehouse every five days. The resulting model can be a solution for sustainable MSMEs.

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