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Dedi Purwanto Indra Kusuma
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RESWARA: Jurnal Riset Ilmu Teknik
Published by Lembaga Penelitian dan Pendidikan (LPP) Kalibra
ISSN : -     EISSN : 30259444     DOI : https://doi.org/10.70716/reswara
Core Subject : Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation
RESWARA: Jurnal Riset Ilmu Teknik is a leading scholarly platform that examines the strategic role of engineering disciplines in advancing the Sustainable Development Goals (SDGs). The journal is dedicated to publishing recent research, innovations, and engineering solutions that support sustainable development. The editorial board welcomes manuscripts based on theoretical frameworks and empirical research. The journal scope covers scientific knowledge and research-based information, including applied research and recent developments in engineering research and development. The primary focus includes Civil Engineering and Spatial Planning, Industrial Engineering, Electrical Engineering and Informatics, Earth Science Technology, and Naval Architecture. All manuscripts published in RESWARA undergo a double-blind peer review process. The final decision on manuscript acceptance rests with the Editorial Board, based on recommendations from independent peer reviewers.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 55 Documents
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Lean Manufacturing Implementation to Reduce Waste in Small-Scale Manufacturing Enterprises Pratama, Ahmad Rizky; Dahab, Amr; Caldera, Savindi
RESWARA: Jurnal Riset Ilmu Teknik Vol. 2 No. 1 (2024): RESWARA: Jurnal Riset Ilmu Teknik, January 2024
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v2i1.377

Abstract

Small-scale manufacturing enterprises (SMEs) face persistent challenges related to inefficiency, high operational costs, and excessive waste generation, which threaten their competitiveness and long-term sustainability. Lean manufacturing has been widely recognized as an effective managerial and operational approach to reduce waste and enhance productivity; however, its implementation in small-scale manufacturing environments remains uneven and context-dependent. This study aims to analyze the implementation of lean manufacturing practices in small-scale manufacturing enterprises and evaluate their effectiveness in reducing operational waste. Using a qualitative case study approach supported by descriptive quantitative indicators, this research synthesizes empirical evidence from multiple manufacturing SMEs. Data were collected through direct observation, semi-structured interviews, document analysis, and performance measurement tools such as Overall Equipment Effectiveness (OEE) and Value Stream Mapping (VSM). The results demonstrate that the systematic application of lean tools—particularly 5S, VSM, Kaizen, and standardized work—significantly reduced non-value-added activities, shortened lead time, and improved equipment efficiency. Comparative analysis with previous studies confirms that lean implementation in SMEs contributes to measurable waste reduction and operational performance improvement, despite constraints related to resources and organizational culture. The study concludes that lean manufacturing is a viable and scalable strategy for small-scale manufacturing enterprises, provided that managerial commitment and continuous improvement culture are effectively cultivated.
Optimization of Inventory Control Using Economic Order Quantity and Safety Stock Approach Saputra, Dwi Putra; Wardhani, Devira Kusuma; Passon, Michael F.
RESWARA: Jurnal Riset Ilmu Teknik Vol. 2 No. 3 (2024): RESWARA: Jurnal Riset Ilmu Teknik, July 2024
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v2i3.378

Abstract

Effective inventory control plays a crucial role in ensuring operational efficiency and cost minimization, particularly in manufacturing, retail, and small–medium enterprises. Inefficient inventory policies often lead to excessive holding costs, frequent stockouts, and unstable production schedules. This study aims to optimize inventory control by integrating the Economic Order Quantity (EOQ) model with safety stock and reorder point approaches. The research adopts a quantitative descriptive design using secondary operational data derived from empirical case studies and prior applications in manufacturing firms, retail businesses, and small enterprises. Inventory parameters such as demand rate, ordering cost, holding cost, lead time, and service level were analyzed using EOQ-based mathematical formulations. The results demonstrate that the integrated EOQ and safety stock model significantly reduces total inventory costs while improving service levels and minimizing stockout risks. Comparative analysis with previous studies indicates consistency with earlier findings across different sectors, confirming the robustness of the model. The study contributes theoretically by consolidating deterministic and probabilistic EOQ perspectives and practically by providing a structured decision-making framework for inventory managers. The findings support the applicability of EOQ-based optimization as a cost-efficient and scalable inventory control strategy suitable for diverse industrial contexts.
Supply Chain Risk Analysis Using Failure Mode and Effect Analysis (FMEA) Lestari, Ayu; Anggara, Rachmat Affriadi; Li, Simon
RESWARA: Jurnal Riset Ilmu Teknik Vol. 2 No. 2 (2024): RESWARA: Jurnal Riset Ilmu Teknik, April 2024
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v2i1.379

Abstract

Supply chain complexity and uncertainty have increased significantly due to globalization, technological interdependence, and recent global disruptions. These conditions expose organizations to various risks that may negatively affect operational performance, resilience, and competitiveness. This study aims to analyze supply chain risks using Failure Mode and Effect Analysis (FMEA) as a systematic and structured risk assessment tool. A qualitative–quantitative research design was employed by identifying potential failure modes across supply chain processes, evaluating their severity, occurrence, and detectability, and calculating the Risk Priority Number (RPN). The analysis demonstrates that FMEA is effective in prioritizing critical risks and supporting decision-making for mitigation strategies. The findings indicate that supplier-related risks, process disruptions, and external shocks such as pandemics and geopolitical conflicts represent the most critical risk categories. Comparative analysis with previous studies confirms that modified and integrated FMEA approaches enhance risk visibility and mitigation effectiveness. This study contributes to the supply chain risk management literature by synthesizing empirical evidence from various industrial contexts and providing a structured framework applicable to both manufacturing and service industries. Practical implications include improved risk prioritization, enhanced supplier evaluation, and stronger organizational resilience.
Productivity Improvement through Work Measurement and Time Study Analysis Ramadhan, Muhammad Fajar; Kukreja, Reena; Duran, Cengiz
RESWARA: Jurnal Riset Ilmu Teknik Vol. 2 No. 3 (2024): RESWARA: Jurnal Riset Ilmu Teknik, July 2024
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v2i3.380

Abstract

Productivity improvement remains a critical concern for manufacturing organizations facing increasing competition, cost pressures, and demand variability. Work measurement and time study techniques have long been recognized as systematic approaches to identifying inefficiencies, standardizing operations, and improving overall productivity. This study aims to analyze the effectiveness of work measurement and time study methods in improving productivity across manufacturing environments. A case-based analytical approach was employed, integrating direct observation, stopwatch time study, work sampling, and motion analysis. Standard times were calculated using performance rating and allowance factors, while bottlenecks and non-value-added activities were identified through detailed process mapping. The results indicate that the application of work measurement and time study techniques can reduce cycle time by 15–35%, improve labor productivity by 10–30%, and enhance line balance and workflow efficiency. Comparative analysis with previous empirical studies confirms the robustness of these methods across diverse industrial contexts, including machining, assembly, furniture, forging, and process industries. The study concludes that systematic work measurement and time study analysis provide practical and theoretically grounded tools for sustainable productivity improvement and operational excellence in manufacturing systems.
Decision Support System for Supplier Selection Using TOPSIS Method Aisyah, Siti Nur; Gunawan, Vera Silvia; El-Sayed, Ahmed Hassan
RESWARA: Jurnal Riset Ilmu Teknik Vol. 2 No. 4 (2024): RESWARA: Jurnal Riset Ilmu Teknik, October 2024
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v2i4.381

Abstract

Supplier selection is a strategic decision that significantly influences organizational performance, cost efficiency, and supply chain sustainability. The increasing complexity of supply chains requires decision makers to evaluate suppliers based on multiple, often conflicting criteria. This study aims to develop a decision support system (DSS) for supplier selection using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. A case study was conducted in a manufacturing company in Indonesia involving five alternative suppliers evaluated against six criteria, including cost, quality, delivery reliability, flexibility, service level, and environmental performance. Data were collected through expert judgment and company procurement records. The TOPSIS method was applied to normalize decision matrices, determine ideal solutions, and calculate preference values for each supplier. The results indicate that TOPSIS effectively ranks suppliers by considering both the closest distance to the ideal solution and the farthest distance from the negative ideal solution. The DSS developed in this study provides a transparent, systematic, and practical tool to support managerial decision-making in supplier selection. The findings confirm that TOPSIS-based DSS can improve objectivity, consistency, and efficiency in procurement decisions. This study contributes to the growing literature on multi-criteria decision-making in supply chain management and offers practical implications for organizations seeking to enhance supplier evaluation processes.
Structural Performance Analysis of Reinforced Concrete Beams under Seismic Load Rahmawati, Siti; Wahnich , Sophie
RESWARA: Jurnal Riset Ilmu Teknik Vol. 2 No. 1 (2024): RESWARA: Jurnal Riset Ilmu Teknik, January 2024
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v2i1.382

Abstract

The seismic performance of reinforced concrete (RC) beams is critical for structural safety in earthquake-prone regions. This study investigates the flexural and lateral behavior of RC beams under seismic loads using a combination of analytical modeling, numerical simulations, and review of contemporary literature. Finite element modeling and pushover analysis were conducted to evaluate displacement, energy dissipation, and ductility of RC beams with conventional and advanced reinforcement detailing (Opabola & Elwood, 2023; Ou et al., 2024; Zhang, 2024). Results indicate that beams with lap-spliced intermediate hoops and strong column-weak beam design significantly enhance residual drift capacity and prevent premature buckling (Sami Aljabbri et al., 2024; Sococol et al., 2022). Numerical simulations demonstrate the influence of reduced cross-sections, bond-slip mechanisms, and engineered cementitious composites on seismic response (Limin et al., 2022; Imamović & Skrinar, 2024; Xiao et al., 2018). Comparisons with experimental data validate the computational models, showing good agreement in predicting lateral displacement and energy dissipation. The study confirms that effective detailing and stiffness optimization improve the seismic resilience of RC beams, providing practical design guidance for structural engineers.
Air Quality Impact Analysis of Traffic Emissions in Metropolitan Areas Lestari, Putri Maharani; Du, Wenjie; Domene, Elena
RESWARA: Jurnal Riset Ilmu Teknik Vol. 2 No. 4 (2024): RESWARA: Jurnal Riset Ilmu Teknik, October 2024
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v2i4.383

Abstract

Urban traffic is a major contributor to air pollution, significantly affecting human health and environmental quality. This study aims to assess the impact of traffic emissions on air quality in metropolitan areas using a synthesis of empirical data and modeling studies. Data from major cities including Shanghai, São Paulo, Barcelona, Delhi, Milan, and Beijing were analyzed, focusing on pollutants such as NO₂, PM2.5, PM10, CO, and black carbon. Methods include emission inventory analysis, deep learning prediction models, bottom-up exposure modeling, and scenario simulations for traffic management interventions. Results indicate that vehicular emissions significantly elevate urban pollutant concentrations, with peak traffic hours and non-exhaust emissions amplifying exposure risks (Du et al., 2022; Pérez-Martínez et al., 2020; Piccoli et al., 2023). Fleet modernization and the adoption of eco-friendly vehicles can reduce NOx and CO concentrations by up to 47% and mitigate public health impacts (Holnicki et al., 2021; 양충헌 et al., 2013). Scenario analysis suggests that cycling promotion and low-emission zones can further improve urban air quality (Kuik et al., 2016; Soret et al., 2023). This study highlights the importance of integrated urban traffic management and policy measures in controlling air pollution.
Design and Performance Analysis of Smart Lighting Systems for Energy Conservation Mansur, Taufik; Parise, Giuseppe; Soheilian, Moe
RESWARA: Jurnal Riset Ilmu Teknik Vol. 2 No. 2 (2024): RESWARA: Jurnal Riset Ilmu Teknik, April 2024
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v2i2.384

Abstract

The rapid growth of urbanization and building infrastructure has increased energy demand, particularly in lighting systems, prompting the development of smart lighting solutions. This study evaluates the design and performance of various smart lighting systems, emphasizing energy efficiency, user comfort, and sustainability. Using a systematic literature review and empirical analysis of published case studies, systems were assessed based on control strategies, sensor integration, and adaptability in different indoor and outdoor environments. Results indicate that occupancy- and daylight-adaptive systems can achieve energy savings between 35% and 82% compared to conventional systems (Mansur et al., 2021; Shahzad et al., 2016). Moreover, smart street and indoor lighting systems incorporating wireless sensor networks, ZigBee mesh networks, and cloud-based control improve operational efficiency and reduce CO2 emissions significantly (Bouzid et al., 2019; Padmini et al., 2022). Comparative analysis of residential and commercial implementations highlights trade-offs between energy efficiency and visual comfort, indicating that multi-sensor systems offer optimal balance (Soheilian et al., 2021; Şimşek & Giray, 2022). The findings provide practical insights for building managers and policymakers aiming to implement sustainable lighting solutions while ensuring occupant satisfaction.
Evaluation of Composting Methods for Organic Waste Reduction Rahadi, Zulfikar; Manea, Elena Elisabeta; Rifai, Rıfat
RESWARA: Jurnal Riset Ilmu Teknik Vol. 2 No. 4 (2024): RESWARA: Jurnal Riset Ilmu Teknik, October 2024
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v2i4.386

Abstract

The rapid increase in organic waste generation has become a critical environmental challenge, particularly in developing countries where landfill dependency remains high. Composting has been widely recognized as a sustainable and cost-effective method for reducing organic waste while producing value-added soil amendments. This study aims to evaluate and compare various composting methods in terms of their effectiveness in organic waste reduction, process efficiency, environmental performance, and socio-economic feasibility. A systematic literature-based evaluation was conducted using qualitative synthesis and comparative analysis of empirical findings from peer-reviewed international journals. The reviewed composting methods include windrow composting, aerobic composting, anaerobic composting, vermicomposting, in-vessel composting, pit composting, and hybrid systems. The results indicate that aerobic-based composting methods, particularly windrow and in-vessel systems, demonstrate higher waste reduction rates (40–95%), faster stabilization, and better compost quality compared to anaerobic and pit-based systems. Hybrid approaches combining windrow and vermicomposting were found to be effective in accelerating maturation and pathogen reduction. Furthermore, technological enhancements such as microbial inoculants and controlled aeration significantly improve composting efficiency. This study concludes that composting is a viable strategy for sustainable organic waste management, although method selection should consider local conditions, waste characteristics, and socio-economic factors. The findings provide valuable insights for policymakers and practitioners seeking to optimize composting systems for sustainable waste reduction.
Development of Web-Based Monitoring Systems for Industrial Equipment Performance Putra, Handoko; Fauziah , Ratna Juwita; Aksa , Karima
RESWARA: Jurnal Riset Ilmu Teknik Vol. 2 No. 1 (2024): RESWARA: Jurnal Riset Ilmu Teknik, January 2024
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v2i1.387

Abstract

The rapid advancement of Industry 4.0 has significantly increased the demand for reliable and scalable monitoring systems to ensure optimal industrial equipment performance. Traditional monitoring approaches are often limited by isolated data acquisition, delayed diagnostics, and insufficient integration with web-based platforms. This study aims to develop and analyze a web-based monitoring system architecture for industrial equipment performance by synthesizing existing monitoring technologies, cloud-based infrastructures, Internet of Things (IoT), and predictive maintenance frameworks. The research adopts a qualitative systematic literature-based development approach by reviewing patents, journal articles, conference proceedings, and industrial case studies related to industrial equipment monitoring systems. The analysis focuses on system architecture, data acquisition mechanisms, communication protocols, dashboard visualization, and performance evaluation methods. The findings indicate that web-based monitoring systems significantly improve real-time visibility, centralized management, and decision-making efficiency. Integration with OPC UA, IoT sensors, cloud platforms, and edge computing enhances scalability, reduces maintenance costs, and enables predictive maintenance strategies. The study concludes that web-based monitoring systems represent a critical foundation for intelligent industrial operations and sustainable equipment management. The proposed conceptual architecture can serve as a reference model for future implementations in manufacturing, energy, and heavy machinery sectors.

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