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Jurnal Rekayasa Sistem Industri
Published by Universitas Katolik Parahyangan
ISSN : 02161036     EISSN : 23391499     DOI : https://doi.org/10.26593/jrsi.v7i1.2798.47-54
Core Subject : Engineering,
Industrial & Manufacturing Engineering
Data and Analytics Decision Analysis E-Business and E-Commerce Engineering Economy and Cost Analysis Human Factors Information Systems Intelligent Systems Manufacturing Systems Operations Research Production Planning and Control Project Management Quality Control and Management Reliability and Maintenance Engineering Safety and Risk Management Service Innovation and Management Supply Chain Management Systems Modeling and Simulation Technology and Knowledge Management
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 360 Documents
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Usulan Peningkatan Efektivitas Mesin Multi Bor dengan Menggunakan Metode Overall Resource Effectiveness dan Failure Mode Effect Analysis Sanjaya, Wahyu Eka Putra; Garside, Annisa Kesy; Wardana, Rahmad Wisnu
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6520.69-78

Abstract

PT XYZ is a company engaged in the wood industry which is marketed for export. In carrying out the production process losses often occur in multi drill machines thereby reducing the effectiveness of the machine. These losses arise because the machine is often adjusted and experiences breakdowns. Therefore, this study will analyze the effectiveness of the multi drill machine using the Overall Resource Effectiveness (ORE) method. Furthermore, fishbone diagrams, Failure Mode Effect Analysis (FMEA), and Total Productive Maintenance will be used as a method for providing improvement suggestions to increase machine effectiveness. From the calculation results, the ORE value is 59.58% (below the standard, which is 85%). Furthermore, by using the fishbone and FMEA methods, 3 failure modes with the largest RPN values were taken. Proposed improvements to increase the effectiveness of multi-bore machines are the application of autonomous maintenance, quality maintenance, preventive maintenance, and provision of safety stock.
Seleksi Jabatan Fungsional Umum Inspektur Bandar Udara Dengan Pendekatan Analytic Hierarchy Process (AHP) Sutikno, Yusak; Saputra, Hendri
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6596.47-58

Abstract

Airport Inspector is a strategic position responsible for carrying out technical guidance activities in regulation, control, supervision, investigation and operational safety services in the airport sector. Therefore, assessing and selecting personnel with appropriate abilities, competencies, and performance is essential to ensure that the right candidate fills this position so that services can be provided optimally. The current selection process is considered to be only administrative, does not reflect the expected competencies and performance, and is less transparent, so the results cannot be accounted for. This research solves this problem by optimizing the selection process using one of the Multi Criteria Decisions Method (MCDM) approaches, the AHP method, where this approach has never been used before. Through AHP, the selection process can be carried out in a more structured, objective, transparent, and intuitive manner as expected. This research optimizes the existing assessment criteria so that all parties can still accept the results: Formal Education, Competency, Years of Service, and Work Performance. The result shows that Work Performance has the highest weighting value (0.513), followed by Competency (0.267), Work Period (0.119), and Formal Education (0.101). The synthesis value of all criteria/sub-criteria shows that Candidate 3 is the highest (scale 1 of 1), then Candidate (0.742 of 1), Candidate 4 (0.726 of 1), and Candidate 1 is the lowest (0.665 of 1).
Penerapan SHERPA untuk Identifikasi Kinerja dan Human Error Pengoperasian Mesin Induk Kapal Penangkap Ikan Yaqin, Rizqi Ilmal; Septianda, Devin; Priharanto, Yuniar Endri; Abrori, M. Zaki Latif
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6681.91-106

Abstract

Occupational accidents due to human errors in the operation of main engines on fishing vessels need to be considered because they can be fatal to the ship. This study aims to identify and analyze critical activities in the operation of fishing vessel main engines using the Systematic Human Error Reduction And Prediction Approach (SHERPA) method. The analytical method is to collect data by observation and interviews to fulfill the SHERPA tabulation. SHERPA analysis is closely related to using Hierarchial Task Analysis (HTA) diagrams to determine the amount of activity generated in the operation of fishing vessel main engines. In addition, work intensity analysis is applied to determine the stages that need to be considered in the operation of the main engine. Based on the resulting analysis, the highest work intensity is at the operating stage of the main engine. At the same time, the critical activity level is in closing the fuel faucet and the cooling system water faucet, which are included in the activity category of turning off the main engine. The findings of this study provide insight into handling critical activities in the operation of the main engine so that a strategy is needed to reduce human error in operation. The strategy for reducing this activity is strictly supervising and modifying or adding tools to make it easier for operators. The investigation results can inform the intensity and critical points of human error in the operation of fishing vessel main engines to reduce the occurrence of work accidents.
Analisis Statik dan Dinamik Struktur Tranduser pada Low-Cost Dynamometer untuk Mengukur Gaya Potong Proses Bubut Orthogonal Alfiyani, Risma; Susanto, Agus; Rezika, Wida Yuliar; Wicaksono, Ramadhana Eka; Mudmainah, Putri Hana Widyaning
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6746.107-116

Abstract

Cutting forces in turning process are usually measured using dynamometer and they can be used to evaluate the quality of the cutting process. Commercial dynamometers on the market today offered with quite expensive prices. Therefore, many researchers are trying to design dynamometers at more affordable prices. One of the most important components in designing a dynamometer is tranducer. This article discusses the design and static and dynamic analysis of a full octagonal shaped ring tranducer for measuring cutting forces in orthogonal cutting. The tranducer design is analysed statically using the Finite Element Method (FEM) and dynamically using the Experimental Modal Analysis (EMA) method to determine its structural strength. The results of the static analysis of the strength of the tranducer structure were able to withstand static loads of 224 to 388 N. It is because the tranducer stress did not exceed the yield strength of the material which is 233 MPa. While the dynamic analysis of the tranducer structure using EMA shows that the natural frequency, the damping ratio, the stiffness constant, the modal mass, and the damping coefficient 3851 Hz, 18.5 x 106 N/m, 1.04%, 32 g, and 16 N/s/m, respectively. With these dynamic parameter, the tranducer design for this low-cost dynamometer is safe and reliable when used in the turning process with spindle rotation speeds reaching 20 Krpm.
Peran Natural Language Processing dalam Proses Pengembangan Produk Baru: Tinjauan Literatur Simanullang, Gerald Shan Benediktus; The, Jin Ai
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6790.117-130

Abstract

Customer satisfaction is a key success factor for a business. To provide products that meet customer satisfaction, companies must be able to understand the customers’ needs and desires. Technological developments nowadays have helped companies to understand customer desires more easily so that companies can provide products that satisfy their customer. Natural Language Processing (NLP) is a technology that allows computers to process human language. NLP is also commonly referred as text-mining. NLP has been utilized in the New Product Development (NPD) process. We compiled studies related to NLP and NPD and conducted a literature review to map out how far NLP has been utilized in NPD processes. We found that in this era of Big Data, current NLP studies most often have the goal to process text data from online reviews on e-commerce and from social media. By using NLP, large amounts of data can produce valuable Voice of Customer (VOC) information for product development. We also found that NLP technology also has been utilized in other NPD processes that do not involve VOC, such as the design stage, document processing, and extraction of requirements in the NPD process.
Analisis Pengaruh Incremental Discount Pada Model Persediaan Multi Item Dengan Faktor Kedaluwarsa dan Kendala Kapasitas Silitonga, Roland; Kristiana, Leo Rama; Abel, Philo
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6840.131-144

Abstract

The retail industry engaged in the pharmaceutical sector such as pharmacies sells various types of medicinal products and medical chemicals with fluctuating demand characteristics. This is due to the emergence of diseases that cannot be predicted with certainty. Inventory management is an important aspect to ensure the availability of medicines when needed while still being able to minimize losses both from retained capital on goods and potential expiration. Medicinal products themselves have a certain shelf-life, so products that have expired cannot be used again and cause losses to company. The form of inventory management policy is the order lot size, time between orders and reorder points. To determine the size of the order lot, in addition to the expiration aspect, the limitations of the warehouse as a place of storage and purchase discount factors need to be considered. The existence of a discount policy from suppliers can be used to minimize purchasing costs which are a component of inventory costs. The form of the discount policy that is generally given is the all-unit discount, but for certain types of products the policy given is an incremental discount. The purpose of this study is to build a multi-item probabilistic inventory model by considering the expiration factor, warehouse capacity constraints, and purchasing discount policies. This research will compare two discount policies, namely incremental discount and all unit discount. Based on the results of the sensitivity analysis, it is known that the model is sensitive to the parameters of unit discount provisions, good goods fraction, and holding costs.
Kumpulan Pengetahuan Teknologi Cloud Computing untuk Sistem Otomasi Manufaktur Tanaya, Prianggada Indra
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6908.79-90

Abstract

The manufacturing sector is grappling with the need to adapt to rapid technological changes, and leveraging cloud computing is becoming crucial for staying competitive and resilient. The presentation of knowledge in this work focuses on highlighting the specific challenges and opportunities in integrating cloud technologies into manufacturing systems. It aims to answer critical questions such as how cloud computing can enhance manufacturing automation, solve problems, and benefit to the industry. The methodology employed in this research takes a comprehensive and top-down approach, aligning and exploring the practical aspects of implementing these X-as-a-Service (XaaS) model in manufacturing setups. The research also acknowledges the shift from legacy Distributed Numerical Control (DNC) systems to modern solutions like MTConnect and Open Platform Communication (OPC) for data exchange in automated manufacturing systems. Emphasizing the important of data collection and real-time monitoring, the study highlights the role of Industrial Internet of Things (IoT) sensors deployed at various points of manufacturing system components (machine tools, spindles, cutting tools, production units, etc.). These sensors capture real-time production and condition data, enabling informed decision-making in manufacturing systems. This research not only presents the latest knowledge but also offers insights into the challenges, strategies, and methodologies involved in the successful integration of cloud-based technology into manufacturing automation systems. It also aims to serve as a valuable resource for manufacturers, researchers, and industry professionals navigating the transformative journey toward cloud-powered manufacturing.
Analisis Sentimen Data Ulasan Pengguna MyPertamina di Twitter dengan Metode Text Mining Hutabarat, Andita Widya Valencia; Adnyani, Ni Luh Saddhwi Saraswati; Suryadi, Kadarsah
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6958.145-154

Abstract

To ensure that the distribution process of subsidized fuel is more well-targeted, PT Pertamina has developed an application called MyPertamina. The increasing number of MyPertamina users has led to an increasing number of reviews related to the use of MyPertamina. Reviews of MyPertamina fill various social media channels, including Twitter. However, the analysis of user perceptions through social media has not been optimal. Therefore, a better user sentiment mapping is needed. This study was conducted to answer this need by building a text mining model and designing a prototype that can extract and analyze sentiments from tweets related to MyPertamina. This research adopts the CRISP-DM methodology, which consists of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The data obtained for model development reached 6,920 tweet data. Each data was classified into one of three sentiment categories, namely positive, negative, and neutral. After data preparation, 2,057 data were used for model development. The models tested in this study consist of Support Vector Machine (SVM), Multinomial Naïve Bayes, Gaussian Naïve Bayes, Long Short-Term Memory (LSTM), and Bidirectional Long Short-Term Memory (Bi-LSTM) algorithms. The model that produced the best evaluation score and was selected for prototype development is the SVM model with an accuracy score of 83.74%, weighted precision of 83.96%, weighted recall of 83.74%, and weighted F1-score of 83.72%. The prototype is used for extracting and predicting sentiment for new datasets, which can then be visualized in the form of graphs and word clouds according to the user's needs.
Mengintegrasikan Prinsip Pembangunan Berkelanjutan dalam Pembelajaran Matematika untuk Merangsang Keterampilan Berkelanjutan pada Generasi Mendatang Lestari, Santi Arum Puspita; Nurapriani, Fitria; Kusumaningrum, Dwi Sulistya
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.7167.1-10

Abstract

This research constitutes a literature review employing a qualitative approach, analyzing scholarly articles, books, and other documents related to sustainable development. This article aims to summarize and analyze previous studies concerning sustainable development in the context of mathematics education, as well as strategies that can be employed to integrate the principles of sustainable education. Integrating the principles of sustainable development into education, including mathematics education, is crucial in fostering a more environmentally responsible society and promoting sustainability across all sectors. However, its implementation remains limited. Educators face various challenges, including a lack of time, resources, and understanding of sustainable education, along with a dearth of supportive teaching materials. The principles of sustainable development can serve as a framework for developing curricula and teaching practices that are more sustainable. Educators can select mathematical problems related to environmental or social issues, discuss relevant mathematical concepts in connection with these problems, and help students comprehend the impact of mathematical decisions on the environment and society. Integrating the principles of sustainable development into mathematics education not only aids in producing a generation with sustainable skills but also motivates students to learn mathematics in more engaging and meaningful ways. A learning approach centered around sustainable development can be an effective way to prepare students for a sustainable future. The article also underscores the necessity for curriculum development, training, and professional advancement for educators.
Pemelajaran Mesin untuk Pengendalian Mutu pada Proses Produksi Tekstil Tradisional Yosephine, Vina Sari; Hanna, Tabitha; Setiawati, Marla; Setiawan, Ari
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.7173.165-174

Abstract

This research is centered on the practical implementation of machine learning and computer vision technologies to enhance production quality control within the traditional textile industry. The traditional textile sector, known for labor-intensive practices, has slowly adapted to digital transformation. We present a practical case study from Bandung, Indonesia, to validate the effectiveness of our approach in real-world textile manufacturing. By emphasizing machine learning and computer vision, this research narrows the gap between traditional textile practices and digitalization, offering tailored solutions for manufacturers seeking to excel in today's rapidly changing global market. The findings provide valuable insights into the challenges and opportunities of using machine learning and computer vision for production quality control in traditional textile manufacturing. The machine learning models in the study showed good accuracy, ranging from 75% to 100% under various lighting conditions in real-world textile manufacturing environments, confirming their suitability for practical quality control applications.

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