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All Journal Jurnal Rekayasa Sistem Industri TELKOMNIKA (Telecommunication Computing Electronics and Control) JIEMS (Journal of Industrial Engineering and Management Systems) Jurnal Ilmiah Teknik Industri Community Empowerment Prosiding Seri Seminar Nasional JURNAL TEKNIK INDUSTRI Jurnal Indonesia Sosial Teknologi Eduvest - Journal of Universal Studies Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Advance Sustainable Science, Engineering and Technology (ASSET) Journal of Current Studies in SDGs Journal of Current Studies in SDGs
Parwadi Moengin
Universitas Trisakti
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Neuroscience Public Health Social Sciences Transportation Other

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Framework Model for Sustainability Reliability Assessment of Clinical Laboratory Equipment in Indonesian Vertical Hospitals: Contributing to SDG 3 Amal Witonohadi; Parwadi Moengin; Emelia Sari; Rianti Dewi Sulamet-Ariobimo
Journal of Current Studies in SDGs Vol. 2 No. 1 (2026): March
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.2.1.155

Abstract

Objective: This study aims to develop a holistic framework for assessing the reliability of clinical laboratory equipment in vertical hospitals in Indonesia. Clinical laboratories play a strategic role in supporting National Health Insurance and in achieving the Sustainable Development Goals (SDGs) across economic, social, and environmental dimensions. Reliable maintenance systems are crucial for ensuring equipment reliability, maintainability, availability, and safety. Method: A comprehensive literature review of international journals was conducted to identify existing models and methodologies for reliability assessment. The proposed framework integrates reliability engineering, sustainability principles, and VUCA (volatility, uncertainty, complexity, ambiguity) concepts. The model consists of sub-assessment sections covering pre-analytical, analytical, and post-analytical stages, as well as equipment reliability, logistics and warehousing, and continuous equipment monitoring. Results: The framework provides a structured approach for identifying factors that influence the reliability of laboratory equipment, enabling effective assessment and problem-solving in clinical laboratories. It facilitates continuous evaluation, supports maintenance planning, and aligns with safety and quality standards. Novelty: Integrating reliability, sustainability, and VUCA concepts into a single, holistic framework for clinical laboratory equipment in Indonesian vertical hospitals. The proposed framework provides practical guidance for hospital policymakers and managers to ensure accurate testing results, optimize equipment performance, enhance patient safety, and support sustainable healthcare operations. By strengthening the reliability of diagnostic services and improving the quality and accessibility of healthcare delivery, this framework contributes to achieving SDG 3 (Good Health and Well-Being).
Analysis of Road User Satisfaction Passing Through The West Boulevard Highway and The Kelapa Gading - Pulo Gebang Toll Road Lisa Andhika Putri; Darmawan Pontan; Parwadi Moengin; Inavonna Inavonna
Eduvest - Journal of Universal Studies Vol. 5 No. 1 (2025): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i1.50378

Abstract

This study aims to analyze the satisfaction level of road users on Jalan Boulevard Barat Raya and the Kelapa Gading - Pulo Gebang Toll Road. Evaluating user satisfaction is crucial for assessing transportation infrastructure performance and prioritizing road maintenance and development. Using a quantitative approach, data was collected through questionnaires distributed to drivers and passengers of private and online four-wheeled vehicles. The research applied the Importance Performance Analysis (IPA) and Customer Satisfaction Index (CSI) methods, focusing on nine indicators from the Indonesian Ministerial Regulation No. 14 of 2017, including requirements, procedures, completion time, costs, service specifications, implementer competence, behavior, complaint handling, and facilities. The CSI results revealed that road users are "Very Satisfied" with both roads, with Jalan Boulevard Barat Raya scoring 90.7% and the Kelapa Gading - Pulo Gebang Toll Road scoring 90.85%. However, IPA analysis identified several variables in quadrant 1, indicating high importance but low performance. These variables include: (B1) reasonable tariffs without additional costs, (PP1) friendly and polite officers handling complaints, (SM1) availability of complaint forums, and (SP1) adequate supporting facilities. These findings highlight areas needing improvement to enhance user satisfaction further. Overall, the study underscores the importance of addressing specific service gaps to maintain high satisfaction levels among road users.
Optimization of Clean Water Supply Fulfillment Strategies at Water Treatment Plants in Industrial Areas Sonia Oktariyanti; Parwadi Moengin
Eduvest - Journal of Universal Studies Vol. 6 No. 5 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i5.52751

Abstract

The growing demand for clean water in industrial areas requires a reliable and sustainable supply system. However, water treatment plants are operating near capacity due to tenant growth, while high energy consumption, chemical cost fluctuations, and reactive maintenance increase operational and maintenance costs. This study aims to identify optimal strategies for meeting clean water demand in industrial water treatment plant service areas by optimizing operational costs and maintaining utility networks, including operations and maintenance (O&M) improvements, small capital expenditure (CAPEX) through supply chain management (SCM) implementation, and large CAPEX such as water treatment plant expansion or new construction. The research employed financial analysis based on present value (PV) and life cycle costing (LCC) with an analysis period of 20 years and a discount rate of 8%, based on historical water treatment plant operational data and investment estimates. Scenario and sensitivity analyses were conducted to strengthen decision-making. The results show that the O&M strategy is the most optimal and highest-priority strategy, as it provides the highest cumulative cost savings without upfront investment, with PV savings on OPEX and MEX of Rp230.07–677.51 million and Rp495.26 million in the moderate scenario, respectively. The small CAPEX strategy yielded a positive net present value (NPV) saving of IDR 51.48 million but was sensitive to initial investment levels and the degree of chemical cost savings. Meanwhile, the large CAPEX strategy has a total life cycle cost of IDR 57,415.00 million and is more appropriate as a medium- to long-term solution for increasing supply capacity and reliability. 
Adaptive trading system for sustainable forex markets Joni Fat; Parwadi Moengin; Pudji Astuti; Sally Cahyati
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 4: August 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i4.27479

Abstract

This study presents a sustainable and ethically aligned algorithmic trading system for the Euro/United States Dollar (EURUSD) currency pair, integrating reinforcement learning (RL) with a Sugeno-type fuzzy inference mechanism. The framework emphasizes responsible AI principles by combining adaptability and interpretability to support transparent and explainable financial decision-making. Historical EURUSD M15 data from 2020 to 2023 were used for training, while 2024 data served for out-of sample testing. The system employs EMA50-based state classification, tabular state–action–reward–state–action or SARSA learning, and a fuzzy logic layer comprising 27 expert-defined rules. During backtesting, the agent executed 785 trades, achieving a net profit of USD 61.85, a profit factor of 1.04, and a balanced win–loss ratio. Risk-adjusted analysis showed moderate resilience (sharpe ratio = 0.53) and a maximum drawdown of 59.74%. The model demonstrated strong equity stability (ESI = 0.9672) and sensitivity to macroeconomic events identified through cumulative sum (CUSUM) analysis. While the system maintained capital preservation and interpretability, responsiveness under volatile conditions requires improvement. Future work will focus on adaptive exit logic, volatility-aware reward mechanisms, and regime-sensitive policy optimization. This study contributes to advancing sustainable, transparent, and risk-aware artificial intelligence (AI) frameworks in algorithmic trading.
Bottleneck Analysis and Improvement in Apparel Manufacturing Production Processes Using Integration Design of Experiments and Discrete Event Simulation Diki Muchtar; Parwadi Moengin; Dadang Surjasa; Sally Cahyati
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i2.3288

Abstract

Bottlenecks in apparel manufacturing often cause unbalanced production flows, increased waiting times, and reduced system performance. This study aims to analyze and eliminate bottlenecks by integrating Design of Experiments (DOE) and Discrete Event Simulation (DES). Four workstations (X1–X4) were selected as experimental factors, while system performance was evaluated using bottleneck indicators across six production stages (Y1–Y6). DOE was used to design capacity scenarios, and DES assessed system performance under each configuration. Results show that partial capacity increases at selected workstations are insufficient to fully eliminate bottlenecks. Complete elimination was achieved only in specific scenarios (Experiments 13–16), where all bottleneck indicators reached zero. Among these, Experiment 13 was identified as the optimal solution, as it eliminated all bottlenecks with the minimum additional capacity. These findings indicate that targeted capacity enhancement at critical workstations is an effective and economical strategy. The integration of DOE and DES proves to be a reliable data-driven approach for identifying bottlenecks and selecting optimal capacity improvements. This study also provides a structured and replicable framework for bottleneck analysis in apparel manufacturing, contributing to the limited application of DOE–DES integration in this sector.
Co-Authors A.A. Ketut Agung Cahyawan W Adi Sucipto, Adi Ahmad Ahmad Amal Witonohadi Amal Witonohadi Amelia Ayuningtyas Bambang Endro Yuwono Dadang Surjasa, Dadang Darmawan Pontan Dhanu Setyo Bekti Dian EP Diki Muchtar Doaly, Carla Olyvia Emelia Sari Fani Puspitasari Fani Puspitasari Gebriel Chandiawan Inavonna Inavonna Joni Fat Lisa Andhika Putri Nadya Adira Fabiani Nilla Nilla Nyoman Rowin Sinaya Prasetyo, Ryan Faza Pudji Astuti Rianti Dewi Sulamet-Ariobimo Sally Cahyati Sari, Feby Kartika Sofia Debi Puspa Sonia Oktariyanti Steven Teja Sucipto Adi Suwiryo Suvalen Suvalen Wahyu Sejati